Last week, I watched Claude make the exact same mistake I’d corrected three days earlier.
Same project. Same codebase. Same error.
I’d spent fifteen minutes explaining why we use prepared statements for database queries—not string concatenation. Claude understood. Claude apologized. Claude fixed it beautifully.
And then, in a fresh session, Claude did it again. Like our conversation never happened.
Here’s the thing: it wasn’t Claude’s fault.
(Stay with me.)
The correction I’d made? It lived and died in that single session. I never added it to my Claude Code rules. Never updated my project guidelines. Never captured what we’d learned together.
So Claude forgot. Because Claude had to forget.
And honestly? I’ve done this more times than I’d like to admit.
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The Uncomfortable Truth About Your Claude Code Rules
You’ve probably got project rules somewhere.
Maybe in a CLAUDE.md file. Maybe in a markdown doc you include at the start of sessions. Maybe scrawled on a Post-it note stuck to your monitor.
(No judgment.)
These rules matter.
They’re the guardrails that keep Claude from hallucinating, making mistakes, or generating code that looks like it was written by someone who’s never seen your codebase before.
But here’s what nobody talks about: most Claude Code rules are frozen in time.
You wrote them once—probably when you were optimistic and caffeinated and full of good intentions. Maybe you updated them once or twice when something broke spectacularly. And then… they fossilized.
Meanwhile, you’re out there learning. Every session teaches you something. Better patterns. Sneaky edge cases. Production bugs that made you question your life choices at 2am.
But none of that learning makes it back into your rules.
Your rules stay stuck at whatever understanding you had on Day One. A Level 5 Charmander trying to fight Level 50 battles.
(More on Pokémon in a minute. I promise this metaphor is going somewhere.)
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The Three Problems That Keep Your Rules Stuck
Let me break down why this happens—because understanding the problem is half the battle.
Problem #1: The Inclusion Tax
You have to remember to add your rules file at the start of every session. Miss it once—maybe you’re rushing, maybe you’re excited about a feature, maybe you just forgot—and suddenly you’re debugging code that violates your own standards.
It’s like having a gym membership you forget to use. The potential is there. The execution… less so.
Problem #2: Context Decay
Even when you do include your rules, long sessions dilute them. By message #50, your carefully crafted “always use prepared statements” guideline has degraded into… whatever Claude feels like doing.
The rules are still technically in the context window. They’re just competing with 47 other messages for Claude’s attention. And losing.
Here’s what that looks like:
Problem #3: The Maintenance Black Hole
Rules should evolve. You know this. I know this. We all know this.
But who actually updates their rules file regularly?
(I’m raising my hand here too. We’re in this together.)
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The CLAUDE.md Trap
Here’s what most developers do—and I get why it seems logical:
They cram everything into CLAUDE.md.
Security rules. Database patterns. API conventions. Coding standards. Error handling preferences. That one weird edge case from six months ago. All of it, stuffed into one giant file that gets loaded at the start of every session.
The thinking makes sense: “Claude will always have my rules!”
The reality?
A 2,000-line CLAUDE.md file burns through your token limits before you even start working.
You’re paying the context tax on every single message—whether you need those rules or not. Working on a simple UI tweak? Still loading all your database migration patterns. Fixing a typo? Still burning tokens on your entire security playbook.
It’s like packing your entire wardrobe for a weekend trip. Sure, you’ll have options. But you’ll also be exhausted before you get anywhere.
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What If Your Rules Could Level Up?
Okay, here’s where the Pokémon thing comes in. (Told you I’d get there.)
Think about how evolution works in Pokémon. A Charmander doesn’t stay a Charmander forever. It battles. It gains experience. It evolves into Charmeleon, then Charizard. Each evolution makes it stronger, better suited for tougher challenges.
What if your Claude Code rules could work the same way?
Every correction you make.
Every “actually, do it this way instead” moment. Every hard-won insight from debugging at 2am. What if all of that could strengthen your rules automatically?
Not stuffed into a bloated CLAUDE.md. Not forgotten when sessions end. Actually captured and integrated into a system that gets smarter over time.
This is possible now. And it’s not even that complicated.
Enter Agent Skills (And Why They Change Everything)
If you haven’t explored Agent Skills yet, here’s the short version: Skills let Claude activate knowledge only when it needs it.
Instead of loading everything upfront—all 2,000 lines of your rules, whether relevant or not—Claude starts by reading just the skill descriptions. A few lines each. When a task triggers a specific skill, then it reads the full details.
Working on database queries? Claude loads the database skill. Building an API endpoint? It loads the API patterns. Simple UI change? It loads… just what it needs for that.
The token savings are significant. Instead of paying for your entire rulebook on every message, you pay for maybe 50 lines of descriptions, plus whatever specific reference you actually need.
But here’s where it gets interesting for our “evolving rules” problem…
The Card Catalog Architecture
Here’s the approach that solves all three problems we talked about earlier:
Structure your skill like a card catalog, not a library.
Your SKILL.md file becomes an index—brief descriptions pointing to reference files. The actual rules live in a references/ folder:
Instead of cramming everything into SKILL.md like this:
## Database Schema Rules
Always use snake_case for table names...
[50 more lines of database rules]
## Firebase Security Rules
Auth patterns must follow...
[40 more lines of Firebase rules]
Your SKILL.md becomes a simple directory:
## Database Schema Rules
See: references/database.md
Guidelines for table naming, migrations, and schema patterns.
## Firebase Security Rules
See: references/security.md
Authentication patterns and Firestore rules structure.
Why does this matter for evolution?
When you capture new insights, they go into the specific reference file—not bloating the main index. Your skill grows by expanding its reference library, not by inflating one massive file.
And when you pair this structure with the build-insights-logger skill? Your rules start updating themselves based on real learnings.
Your Charmander starts evolving.
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Building Your Self-Evolving Skill: The Complete Walkthrough
Alright, let’s get practical. Here’s exactly how to set this up—step by step, with real screenshots from when I did this myself.
Step 1: Convert Your Existing Rules to an Indexed Skill
If you already have Claude Code rules somewhere (in CLAUDE.md, a rules file, or scattered notes), this is your starting point.
Here’s the prompt I used:
Convert the following project rules at @notes/rules.md into a live documentation skill using the "skill-creator" skill.
## Requirements
### 1. Skill Structure
Create a skill folder with this structure:
```
.claude/skills/[skill-name]/
├── SKILL.md # Index file (card catalog, NOT the full library)
├── references/ # Detailed rule files
│ ├── [category-1].md
│ ├── [category-2].md
│ └── ...
└── [README.md](http://README.md) # Optional: skill usage guide
```
### 2. SKILL.md Design (The Index)
The SKILL.md should act as a **card catalog**, not contain the full rules.
Example:
```
[...content of SKILL.md...]
## Quick Reference
Brief overview of what this skill covers (2-3 sentences max).
## Rule Categories
### [Category 1 Name]
Brief description (1 line). See: `references/[category-1].md`
### [Category 2 Name]
Brief description (1 line). See: `references/[category-2].md`
[Continue for all categories...]
## When to Load References
- Load `references/[category-1].md` when: [specific trigger]
- Load `references/[category-2].md` when: [specific trigger]
```
### 3. Reference File Design
Each reference file in `references/` should:
- Focus on ONE category/domain of rules
- Include code examples where helpful
- Be self-contained (can be understood without reading other files)
- End with a "Quick Checklist" for that category
### 4. Evolvability
Structure the skill so new learnings can be easily added:
- Each reference file should have a `## Lessons Learned` section at the end (initially empty)
- The SKILL.md index should be easy to extend with new categories
- Use consistent formatting so automated updates are possible
## Notes
- Prioritize token efficiency: Claude should only load what it needs
- Keep SKILL.md under 100 lines if possible
- Each reference file should be focused (ideally under 200 lines)
- Use the indexed structure so the build-insights-logger can update specific reference files later
Two prerequisites before you run this:
Install the “skill-creator” skill first
Turn on Plan Mode (Shift+Tab)
Claude initiates the skill-creator and starts working:
It explores your codebase for existing patterns to follow. (I love watching this part—it’s like Claude doing research before diving in.)
In my case, Claude asked clarifying questions before finalizing the plan. This is Plan Mode doing its job—thinking before coding:
After answering, Claude proposed a complete plan:
The plan includes the SKILL.md design—notice how it acts as an index, not a container for all the rules:
I agreed to proceed with auto-accept edits. And here’s what Claude created:
The result:
SKILL.md: 83 lines (the index/card catalog)
15 reference files, each under 200 lines
Every reference file includes code examples, a Quick Checklist, and an empty Lessons Learned section
Those empty Lessons Learned sections? They’re intentional. That’s where the evolution happens.
👉 Don’t have existing rules to convert? You can ask Claude to analyze your codebase and extract patterns into a skill. Or check out my previous post on how to compile your own project rules first.
Step 2: Install the Build-Insights-Logger
This is the skill that captures learnings during your sessions and routes them to the right place.
(Yes, I built this. Yes, I’m biased. But it solves a real problem.)
Step 3: Work Like You Normally Would
Here’s the beautiful part: you don’t need to change how you work.
With your skill installed and the insights logger ready, just… build. Code. Debug. Do your thing.
I’ll show you what this looks like. I asked Claude to audit my WordPress plugin for security vulnerabilities:
Claude found several issues, fixed them, and documented the changes. Standard stuff.
But here’s where it gets good.
After the implementation, I triggered the insights logger:
Please jot down what you have learned so far using the "build-insights-logger" skill.
Claude activated the skill:
And logged 6 insights from the session:
Six insights. Automatically categorized. Saved to .claude/insights/session-2026-01-05-143600.md.
No manual documentation. No “I should write this down” that never happens. Just… captured.
Step 4: Review and Integrate (The Curation Step)
You can review immediately after one session, or batch multiple sessions together. I usually wait until I have a few sessions worth of insights—but that’s personal preference.
Here’s how to review:
Please use the "build-insights-logger" skill to review the insights logged so far.
Claude reads all session files and presents a summary organized by category:
Now here’s the critical part: don’t add everything.
This is where human judgment matters. Review each insight and ask: “Will this apply to future projects, or is it specific to this one-off feature?”
Some insights are gold. Some are situational. You’re the curator here.
I selected insights 1, 2, 5, and 6—the ones that generalize across WordPress projects:
Important detail: Notice my instruction. By default, the build-insights-logger updates CLAUDE.md. I explicitly redirected it to update the skill instead, with a reminder to keep SKILL.md clean—insights should go to the relevant reference files, not the index.
Claude reads the relevant reference files and adds the insights where they belong:
The session file gets archived. And your skill is now smarter than it was an hour ago.
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What You Actually Built Here
Let’s step back for a second.
Four steps. That’s all it took:
Convert rules to an indexed skill
Install the insights logger
Build like normal
Review and integrate learnings
But what actually changed?
You’re no longer maintaining documentation. You’re growing a knowledge base.
Every correction you make—every “actually, do it this way instead” moment, every insight from debugging at 2am—the system captures it. You review it. The good stuff evolves your skill. Your next session starts with rules that reflect what you actually learned, not what you thought you knew when you started.
The gap between your experience and your documentation? It closes.
That mistake I mentioned at the beginning—Claude repeating an error I’d already corrected? It doesn’t happen anymore. Because the correction made it into my Claude Code rules. Automatically. As part of my normal workflow.
Your Charmander evolved into Charizard.
And it keeps evolving.
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Your Turn
If you’ve been cramming rules into CLAUDE.md—or worse, keeping them in your head and hoping for the best—try this process on your next project.
Start with whatever rules you have. Even messy ones. (Especially messy ones, honestly.)
Convert them to an indexed skill. Install the insights logger. Build for a few sessions. Then review your insights folder.
You’ll be surprised at what Claude captured. And you’ll be amazed at how much smarter your rules become when they’re allowed to learn alongside you.
Imagine trying to teach someone to cook over the phone.
You’re walking them through your grandmother’s pasta recipe—the one with the garlic that needs to be just golden, not brown. You describe every step perfectly. The timing. The technique. The little flip of the wrist when you toss the noodles.
And then they say: “It’s burning. What do I do?”
Here’s the thing: you can’t help them. Not really. Because you can’t see the pan. You can’t see how high the flame is. You can’t see that they accidentally grabbed the chili flakes instead of oregano. All you have is their panicked description and your best guess about what might be going wrong.
This, my friend, is exactly what happens when you ask Claude Code to fix a bug.
(Stay with me here.)
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The Merry-Go-Round Nobody Enjoys
You’ve been on this ride before. I know you have.
You describe the bug to Claude. Carefully. Thoroughly. You even add screenshots and error messages because you’re a good communicator, dammit.
Claude proposes a fix.
You try it.
It doesn’t work.
So you describe the bug again—this time with more adjectives and maybe a few capitalized words for emphasis. Claude proposes a slightly different fix. Still broken. You rephrase. Claude tries another angle. Round and round we go.
This is the debugging merry-go-round, and nobody buys tickets to this ride on purpose.
The instinct—the very human instinct—is to blame the AI.
“Claude isn’t smart enough for this.”
“Maybe I need a different model.”
“Why can’t it just SEE what’s happening?”
That last one?
That’s actually the right question.
Just not in the way you think.
Here’s what I’ve learned after spending more time than I’d like to admit arguing with AI about bugs: Claude almost never fails because it lacks intelligence. It fails because it lacks visibility.
Think about what you have access to when you’re debugging. Browser dev tools. Console logs scrolling in real-time. Network requests you can inspect. Elements that highlight when you hover. The actual, living, breathing behavior playing out on your screen.
What does Claude have?
The code. Just the code.
That’s it.
You’re asking a brilliant chef to fix your burning pasta—but they can only read the recipe card. They can’t see the flame. They can’t smell the smoke. They’re working with incomplete information and filling in the gaps with educated guesses.
Sometimes those guesses are right. (Claude is genuinely brilliant at guessing.)
Most of the time? Merry-go-round.
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The Two Bugs That Break AI Every Time
After countless Claude Code debugging sessions—some triumphant, many humbling—I’ve noticed two categories that consistently send AI spinning:
The Invisible State Bugs
React’s useEffect dependencies.
Race conditions. Stale closures. Data that shapeshifts mid-lifecycle like some kind of JavaScript werewolf. These bugs are invisible in the code itself. You can stare at the component for hours (ask me how I know) and see nothing wrong. The bug only reveals itself at runtime—in the sequence of events, the timing of updates, the order of renders.
It’s happening in dimensions Claude can’t perceive.
The “Wrong Address” Bugs
CSS being overridden by inline JavaScript. WordPress functions receiving unexpected null values from somewhere upstream. Error messages that point to line 7374 of a core file—not your code, but code three function calls removed from the actual problem.
The error exists.
But the source? Hidden in cascading calls, plugin interactions, systems talking to systems.
Claude can’t solve either category by reading code alone.
So what do we do?
We give Claude eyes.
(I told you to stay with me. Here’s where it gets good.)
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Method 1: Turn Invisible Data Into Evidence Claude Can Actually See
Let me walk you through a real example.
Because theory is nice, but showing you what this looks like in practice? That’s the good stuff.
I had a Products Browser component. Simple filtering and search functionality—the kind of thing you build in an afternoon and then spend three days debugging because life is like that sometimes.
Each control worked beautifully in isolation:
Search for “apple” → Three results. Beautiful.
Filter by “laptops” → Five results. Chef’s kiss.
But combine them?
Search “apple” + category “laptops” → Broken. The filter gets completely ignored, like I never selected it at all.
Classic React hook dependency bug.
If you’re experienced with React, you spot this pattern in your sleep. But if you’re newer to the framework—or if you vibe-coded this component and touched a dozen files before realizing something broke—you’re stuck waiting for Claude to get lucky.
I spent three rounds asking Claude to fix it. Each fix addressed a different theoretical cause. None worked.
That’s when I stopped arguing and started instrumenting.
Step 1: Ask Claude to Add Logging (Not Fixes)
Instead of another “please fix this” prompt, I asked Claude to help me see what was happening:
Notice what I didn’t say: “Fix this bug.”
What I said: “Add logging to track data changes.”
This is the mindset shift that changes everything.
Claude added console.log statements to every useEffect that touched the view state:
Each log captured which effect triggered, what the current values were, and what got computed. Basically, Claude created a running transcript of everything happening inside my component’s brain.
Step 2: Run the Test and Capture What You See
I opened the browser, selected “laptops” from the category filter, then typed “apple” in the search box.
The console lit up like a Christmas tree of evidence.
Step 3: Feed the Logs Back to Claude
Here’s where the magic happens. I copied that console output—all of it—and pasted it directly into Claude:
And Claude? Claude saw everything:
Claude found the bug immediately.
The logs revealed the whole story: when I selected a category, useEffect:filters fired and correctly filtered the products. But then when I typed in the search box, useEffect:search fired—and it ran against the full product list, completely ignoring the category filter.
The search effect was overwriting the filter results.
Last effect wins. (JavaScript, you beautiful chaos gremlin.)
Claude proposed the fix: replace multiple competing useEffect hooks with a single useMemo that applies all transforms together:
The difference between “Claude guessing for 20 minutes” and “Claude solving it instantly” was 30 seconds of logging.
That’s not hyperbole. That’s just… math.
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Method 2: Map the Problem Before Anyone Tries to Solve It
The second method works for a different beast entirely—the kind of bug where even the error message is lying to you.
Here’s a WordPress error that haunted me for hours:
Deprecated: strpos(): Passing null to parameter #1 ($haystack) of type string
is deprecated in /var/www/html/wp-includes/functions.php on line 7374
Warning: Cannot modify header information - headers already sent by
(output started at /var/www/html/wp-includes/functions.php:7374)
in /var/www/html/wp-includes/option.php on line 1740
If you’ve done any WordPress development, you recognize this particular flavor of suffering.
The error points to core WordPress files—not your code. Something, somewhere, is passing null to a function that expects a string. But where? The error message is about as helpful as a fortune cookie that just says “bad things happened.”
I’d made changes to several theme files.
Any one of them could be the culprit.
And the cascading nature of WordPress hooks meant the error could originate three or four function calls before the actual crash.
After a few rounds of Claude trying random fixes (bless its heart), I tried something completely different.
The Brainstorming Prompt That Changes Everything
Instead of “fix this,” I asked Claude to brainstorm debugging approaches—and to visualize them with ASCII diagrams.
(I know. ASCII diagrams. In 2025. But stay with me, because this is where Claude Code debugging gets genuinely interesting.)
Claude Maps the Error Chain
Claude started by analyzing the flow of the problem:
The diagram showed exactly what was happening: some theme code was passing null to WordPress core functions, which then passed that null to PHP string functions, which threw the deprecation warning.
But which theme code? Claude identified the suspect locations:
Four possible sources.
Each with code examples showing what the problematic pattern might look like.
This is Claude thinking out loud, visually. And it’s incredibly useful for Claude Code debugging because now we’re not guessing—we’re investigating.
Multiple Debugging Strategies (Not Just One)
Rather than jumping to a single fix and hoping, Claude laid out several approaches:
Option A: Search all filter callbacks for missing return statements.
Option B: Find which WordPress functions use strpos internally.
Option C: Add debug_backtrace() at the error point to trace the caller.
Option D: Search for common patterns like wp_redirect with variables.
Four different angles of attack.
This is what systematic debugging looks like—and it’s exactly what you need when you’re stuck in the merry-go-round.
Claude Does Its Homework
Here’s where Opus 4.5 surprised me.
Instead of settling on the first approach, it validated its theories by actually searching the codebase:
It searched for wp_redirect calls, add_filter patterns, get_option usages—systematically eliminating possibilities like a detective working through a suspect list.
Then it updated its diagnosis based on what it found:
The investigation narrowed.
The error was coming from path-handling functions—something was returning a null path where a string was expected.
The Summary That Actually Leads Somewhere
Claude concluded with a clear summary of everything we now knew:
And multiple approaches to fix it, ranked by how surgical they’d be:
Did it work?
First attempt. Approach A—adding a debug backtrace—immediately revealed a function in FluentCartBridge.php that was returning null when $screen->id was empty.
One additional null check.
Bug gone.
All those rounds of failed attempts? They were doomed from the start because Claude was guessing blindly. Once it could see the error chain visually—once it had a map instead of just a destination—the solution was obvious.
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Why This Actually Works (The Part Where I Get a Little Philosophical)
Both of these methods work because they address the same fundamental gap in Claude Code debugging: AI doesn’t fail because it’s not smart enough. It fails because it can’t see what you see.
When you’re debugging, you have browser dev tools, console logs, network requests, and actual behavior unfolding on your screen. Claude has code files.
That’s it.
It’s working with incomplete information and filling the gaps with educated guesses.
Here’s the mindset shift that changed everything for me:
👉 Stop expecting AI to figure it out. Start helping AI see what you see.
You become the eyes. AI becomes the analytical brain that processes patterns and proposes solutions based on the evidence you feed it.
It’s a collaboration. A partnership. Not a vending machine where you insert a problem and expect a solution to drop out.
When to Use Logging
Add logs when the bug involves:
Data flow and state management
Timing issues and race conditions
Lifecycle problems in React, Vue, or similar frameworks
Anything where the sequence of events matters
The logs transform invisible runtime behavior into visible evidence.
React’s useEffect, state updates, and re-renders happen in milliseconds—too fast to trace mentally, but perfectly captured by console.log. Feed those logs to Claude, and suddenly it can see the movie instead of just reading the script.
When to Use ASCII Brainstorming
Use the brainstorming approach when:
Error messages point to the wrong location
The bug could originate from multiple places
You’ve already tried the obvious fixes (twice)
The problem involves cascading effects across systems
Asking Claude to brainstorm with diagrams forces it to slow down and map the problem systematically. It prevents the merry-go-round where AI keeps trying variations of the same failed approach. By exploring multiple angles first, you often find the root cause on the very first real attempt.
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The Line Worth Tattooing Somewhere (Metaphorically)
Here’s what I want you to take away from all of this:
Don’t argue with AI about what it can’t see. Show it.
The next time Claude can’t solve a bug after a few rounds, resist the urge to rephrase your complaint. Don’t add more adjectives. Don’t type in all caps. (I know. I KNOW. But still.)
Instead, ask yourself: “What am I seeing that Claude isn’t?”
Then find a way to bridge that gap—through logs, through diagrams, through screenshots, through any method that gives AI the visibility it needs to actually help you.
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Your Next Steps (The Warm and Actionable Version)
For state and timing bugs:
Pause. Take a breath. Step off the merry-go-round.
Ask Claude to add logging that tracks the data flow.
Run your test, copy the console output, paste it back to Claude.
Watch Claude solve in one shot what it couldn’t guess in twenty.
For complex, cascading bugs:
Paste the error message (yes, the whole confusing thing).
Add: “Let’s brainstorm ways to debug this. Use ASCII diagrams.”
Let Claude map the problem before it tries to solve it.
Pick the most surgical approach from the options it generates.
That bug that’s been driving you up the wall? The one Claude keeps missing?
I was bouncing between ChatGPT Pro, Claude web, and Cursor like a pinball with a deadline. Copy from o1 pro. Paste into my editor. Fix the bug it introduced. Pray it works. Try Cursor for a second opinion. Watch it rewrite my entire file when I asked for one measly line.
Rinse. Repeat. Question your life choices.
(We’ve all been there. And if you say you haven’t, well, I’m not sure I believe you.)
Then May hit. Anthropic added Claude Code to their Max plan—same $200/month I was already burning on ChatGPT Pro, but now I could stop copy-pasting and start orchestrating.
That shift changed everything.
Here’s the thing: I wrote 30+ articles this year documenting every breakthrough, every spectacular failure, every “wait, that’s how it’s supposed to work?” moment. If you only read one piece from me in 2025—make it this one.
What follows are the 4 immutable laws of Vibe Coding I discovered this year. They turned chaotic AI sessions into systematic, predictable wins. Once you see them, you can’t unsee them.
Ready? Let’s go.
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Rule #1: The Blueprint Is More Important Than The Code
Let me tell you about the single biggest mistake I see developers make.
They type “build me a task management app” and hit Enter. Claude generates code. Components. Database schemas. Authentication logic.
And then… it’s nothing like what they imagined.
They blame the AI. “It hallucinated again.”
But here’s what I’ve learned after shipping dozens of projects with Claude Code: hallucinations are usually just ambiguity in your prompt. That’s it. That’s the secret nobody wants to admit.
AI is a terrible architect. Give it vague instructions, and it fills in the blanks with whatever patterns it’s seen most often. (Which, spoiler alert, aren’t YOUR patterns.)
But AI is an amazing contractor.
Give it clear blueprints—specific requirements, explicit constraints, visual references—and it executes with surgical precision. Like a really talented carpenter who just needs you to stop saying “make it nice” and start handing over actual measurements.
The technique: Interview yourself first
Instead of asking Claude to “build me an app,” I use a brainstorming prompt (inspired by McKay Wrigley and Sabrina Ramonov) that flips the entire script.
The AI interviews me.
“What’s the core problem this solves?”
“Who uses it?”
“What does the main screen look like?”
“What happens when the user clicks X?”
By the time I’ve answered those questions, I’ve got a Product Requirements Document. Not AI-generated slop—my vision, clarified.
Claude becomes the junior dev who asks great questions before writing a single line of code. I stay the architect who actually understands what we’re building.
(This is the way it should be.)
The secret weapon: ASCII wireframes
Text descriptions get misinterpreted. Every. Single. Time.
You say “a sidebar with navigation.” Claude hears “full-width hamburger menu.”
So I started including ASCII art wireframes in my prompts:
Sounds primitive, right? Almost embarrassingly low-tech.
The results say otherwise.
When I started including visual plans, my first-try success rate hit 97%. Claude understood layout and hierarchy immediately. No more “that’s not what I meant” rewrites. No more three rounds of “closer, but still wrong.”
👉 The takeaway: Stop typing code and start drawing maps. The blueprint is where the real work happens.
Rule #2: Separate The “Thinker” From The “Builder”
At the beginning, I was using Claude Code for everything.
Planning. Building. Reviewing. Debugging.
One model to rule them all.
And it almost worked.
Almost.
But I kept running into the same problems. Claude would rewrite perfectly good code. Add complex abstractions I never asked for. Solve a simple bug by restructuring half my app.
I asked for email OTP login. I got a 12-file authentication framework.
I asked to fix a type error. Claude decided my entire architecture was wrong.
(It wasn’t. I promise you, it wasn’t.)
The discovery: Specialized roles
Then I stumbled onto a workflow that changed everything—and honestly, I felt a little silly for not seeing it sooner.
Use one model to think. Use another to build.
For me, that’s GPT-5/Codex (The Thinker) and Claude Code (The Builder).
Codex asks clarifying questions. It creates comprehensive plans. It reviews code like a senior engineer who’s seen every possible edge case and still remembers them all.
Claude Code executes. Fast. Reliably. It handles files, terminal commands, and edits without wandering off into philosophical debates about code architecture.
Together? Magic.
The review loop
The workflow looks like this:
Plan (Codex): Describe what I want to build. Codex asks questions, creates a detailed implementation plan.
Build (Claude Code): Feed the plan to Claude. Let it execute.
Review (Codex): Paste the implementation back to Codex. It checks against the original plan, catches bugs, finds edge cases.
That third step—the review loop—catches issues that single-model workflows miss every time. EVERY time.
Taming the overengineering monster
Claude has a tendency to overcomplicate. It’s well-documented at this point. (If you’ve used it for more than a week, you know exactly what I’m talking about.)
My fix? The Surgical Coding Prompt.
Instead of “add this feature,” I tell Claude:
“Analyze the existing patterns in this codebase. Implement this change using the minimal number of edits. Do not refactor unless explicitly asked. Show me the surgical changes—nothing more.”
From 15 files to 3 files. From 1000+ lines to 120 lines.
Same functionality. 90% less complexity.
👉 The takeaway: Treat your AI models like a team, not a swiss-army knife. Specialized roles produce specialized results.
“Why do I keep explaining the same patterns over and over?”
Every new project, I’d spell out my authentication approach. My database schema conventions. My error handling patterns. Every. Single. Time.
Claude would forget by the next session. Sometimes by the next prompt.
I was treating AI like a goldfish with a keyboard.
(No offense to goldfish. They’re trying their best.)
The “I know kung fu” moment
Then Claude launched Skills—and everything clicked.
Skills let you package your coding patterns into reusable modules. Instead of explaining “here’s how I do authentication” for the 47th time, you create an auth-skill. Enable it, and Claude instantly knows your entire implementation.
The exact patterns. The exact folder structure. The exact error messages.
Every project uses the same battle-tested approach. Zero drift. Zero “well, last time I used a different library.”
It’s like downloading knowledge directly into Claude’s brain.
Matrix-style. (Hence the name.)
Building your first skill
The process is stupidly simple:
Take code that already works in production
Document the patterns using GPT-5 (it’s better at documentation than execution)
Transform that documentation into a Claude Skill using the skill-creator tool
Deploy to any future project
The documentation step matters. GPT-5 creates clean, structured explanations of your existing implementations. Claude Skills uses those explanations to replicate them perfectly.
The compound learning effect
Here’s where it gets really interesting.
I built an Insights Logger skill that captures lessons while Claude “code”. Every architectural decision, every weird bug fix, every “oh that’s why it works that way” moment—automatically logged.
At the end of each session, I review those insights. The good ones get promoted to my CLAUDE.md file—the permanent knowledge base Claude reads at the start of every project.
Each coding session builds on the last. Compound learning, automated.
👉 The takeaway: Prompting is temporary. Skills are permanent. If you’re explaining something twice, you’re doing it wrong.
Rule #4: Friction Is The Enemy (So Automate It Away)
Let me describe a scene you’ll recognize.
You’re deep in flow state. Claude Code is humming along. Building components, wiring up APIs, making real progress.
And then:
Allow Claude to run `npm install`? [y/n]
You press Enter.
Allow Claude to run `git status`? [y/n]
Enter.
Allow Claude to run `ls src/`? [y/n]
Enter. Enter. Enter. Enter. Enter.
By prompt #47, you’re not reading anymore. You’re a very tired seal at a circus act nobody asked for.
(Stay with me on this metaphor—it’s going somewhere.)
Anthropic calls this approval fatigue. Their testing showed developers hit it within the first hour of use.
And here’s the terrifying part: the safety mechanism designed to protect you actually makes you less safe. You start approving everything blindly. Including the stuff you should actually read.
The sandbox solution
Claude Code’s sandbox flips the entire model.
Instead of asking permission for every tiny action, the sandbox draws clear boundaries upfront. Work freely inside them. Get blocked immediately outside them.
On Linux, it uses Bubblewrap—the same tech powering Flatpak. On macOS, it’s Seatbelt—the same tech restricting iOS apps.
These boundaries are OS-enforced. Prompt injection can’t bypass them.
Claude can only read/write inside your project directory. Your SSH keys, AWS credentials, shell config? Invisible. Network traffic routes through a proxy allowing only approved domains.
You run /sandbox, enable auto-allow mode, and suddenly every sandboxed command executes automatically. No prompts. No friction. No approval fatigue.
The 84% reduction in permission prompts? Nice. The kernel-level protection that actually works? Essential.
Parallel experimentation with Git Worktrees
Here’s another friction point that kills vibe coding: fear of breaking the main branch.
My fix: Git Worktrees with full isolation.
Standard worktrees share your database. They share your ports. Three AI agents working on three features leads to chaos. (Ask me how I know.)
I built a tool that gives each worktree its own universe. Own working directory. Own PostgreSQL database clone. Own port assignment. Own .env configuration. Now I run three experimental branches simultaneously. Let three Claude instances explore three different approaches. Pick the winner. Delete the losers.
No conflicts. No fear. No “let me save my work before trying this crazy idea.”
👉 The takeaway: Safe environments allow for dangerous speed. Eliminate friction, and experimentation becomes free.
Ready to set it up?
Claude Code Sandbox Explained walks through the complete configuration—including battle-tested configs for Next.js, WordPress, and maximum paranoia mode.
The Synthesis: What Separates Hobbyists From Shippers
These 4 rules are what separate “people who play with AI” from “people who ship software with AI.”
Rule #1: The blueprint is more important than the code.
Rule #2: Separate the thinker from the builder.
Rule #3: Don’t just prompt—teach skills.
Rule #4: Friction is the enemy.
Each rule builds on the last.
Clear blueprints feed into specialized models. Specialized models benefit from reusable skills. Reusable skills only matter if friction doesn’t kill your flow.
It’s a system. Not a collection of random tips.
Where to start
Don’t try to implement all four at once.
That’s a recipe for burnout.
Start with Rule #4. Enable the sandbox. Regain your sanity. Stop being a tired circus seal.
Then move to Rule #1. Before your next feature, write the PRD first. Interview yourself. Draw the ASCII wireframe.
Rule #2 and Rule #3 come naturally after that. You’ll feel the pain of overengineering (and want specialized roles). You’ll get tired of repeating yourself (and want skills).
The system reveals itself when you need it.
Your challenge for 2026
Pick one project you’ve been putting off. Something that felt too complex for AI assistance.
Apply Rule #1: Write the blueprint first. ASCII wireframes and all.
Apply Rule #4: Set up the sandbox before you start.
Then let Claude execute.
Watch what happens when AI has clear boundaries and clear instructions. Watch how different it feels when you’re orchestrating instead of babysitting.
What will you build first?
Here’s to an even faster 2026.
Now go ship something.
This post synthesizes a year’s worth of vibe coding experimentation. Browse the full archive to dive deeper into any technique—from CLAUDE.md setup to sub-agent patterns to WordPress automation.
Claude Code is humming along—building your Next.js app, spinning up components, mapping out API routes, sketching database schemas. It’s beautiful. It’s efficient. It’s everything you dreamed AI-assisted coding could be.
And then.
Allow Claude to run `npm install`? [y/n]
You press Enter.
Allow Claude to run `git status`? [y/n]
You press Enter.
Allow Claude to run `ls src/`? [y/n]
Enter. Enter. Enter. Enter. Enter.
By prompt #47, you’re not even reading anymore. You’re just… pressing Enter. Like a very tired seal at a circus act nobody asked for.
Here’s the thing: that permission system was designed to protect you. And instead? It’s training you to ignore it entirely.
Let’s fix that.
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The Paradox Nobody Talks About
I want you to sit with this for a second—because it’s genuinely wild when you think about it.
Claude Code’s safety system was built with good intentions. Ask before every risky action. Sounds reasonable, right? Sounds responsible.
But here’s what actually happens in the wild:
The safety mechanism designed to protect you makes you less safe.
Anthropic’s own testing confirmed this. They call it “approval fatigue.” And their data showed developers hit it within the first hour of use.
(Within the first hour. Not after weeks of grinding. One. Hour.)
Sound familiar?
Yeah. I thought so.
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The Fix: Boundaries, Not Babysitting
Here’s where Claude Code Sandbox comes in—and it flips the entire model on its head.
Instead of asking permission for every tiny thing (like an overly anxious intern double-checking if it’s okay to use the stapler), the sandbox draws clear boundaries upfront. Work freely inside them. Get blocked immediately outside them.
Think of it like giving Claude a room to work in—not the keys to the whole house.
Inside that room? Full autonomy. Zero prompts. Go nuts.
Outside that room? Blocked. Immediately. At the operating system level.
Two Invisible Walls
Here’s what the sandbox actually does:
Wall 1: Filesystem Isolation
Claude can only read and write inside your project directory. Everything else—your SSH keys, AWS credentials, shell config—is invisible. Not just “blocked.” Invisible. Like it doesn’t exist. (Which, for Claude’s purposes, it doesn’t.)
Wall 2: Network Isolation
All network traffic routes through a proxy that only allows approved domains. npm install needs registry.npmjs.org? You approve it once. Some sketchy postinstall script tries to phone home to evil.com? Blocked. Immediately. No drama.
Why This Actually Works (And Why It’s Different)
Stay with me here—because this is the part that matters.
These aren’t application-level restrictions. They’re operating system enforced.
On Linux, Claude Code uses Bubblewrap—the same tech that powers Flatpak. On macOS, it’s Seatbelt—the same tech that restricts iOS apps.
This means even if a malicious prompt injection tricks Claude into trying to read your SSH keys… it physically cannot. The kernel blocks it. Full stop.
Prompt injection can’t bypass OS-level security.
That’s the whole point. That’s what makes this different from “please be good” security theater.
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Quick Start: 5 Minutes to Actual Protection
Alright. Enough theory. Let’s get you set up.
Step 1: Enable Sandbox
In Claude Code, type:
/sandbox
Select Auto-allow mode.
This is the sweet spot: sandboxed commands run automatically, unsandboxed actions still prompt you. Best of both worlds.
If it executes without prompting? Sandbox is working.
That’s it. OS-level protection with zero friction for normal work.
(I know, I know—it almost feels too easy. It’s not a trick. It just… works.)
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Real-World Configurations You Can Steal
The basic setup handles most projects beautifully. But different stacks have different quirks.
Docker can’t run inside a sandbox. Dev servers need to bind ports. Private registries need network access. You know how it goes.
Here are three battle-tested configs. Find the one closest to your setup, copy-paste, adjust as needed.
Scenario 1: Web Development (Next.js, Vite, React)
The Problem: You run npm run dev inside sandbox and… nothing happens. On macOS, the sandbox blocks port binding by default. Your dev server can’t start. Cue frustration.
What this does:allowLocalBinding: true fixes the macOS dev server issue. npm/npx/node commands run automatically (sandboxed). Your .env files stay invisible to Claude. And it still asks before publishing to npm or pushing to git—because those are the “are you really sure?” moments.
Zero prompts for normal work. Full protection. Still asks before the dangerous stuff.
Scenario 2: WordPress with Docker and wp-env
WordPress development is trickier. Tools like wp-env and docker-compose fundamentally don’t work inside a sandbox—Docker needs to talk to the Docker daemon through a Unix socket, and the sandbox blocks socket access.
The trade-off: Docker runs unsandboxed. That’s less secure—I won’t pretend otherwise.
But here’s the thing: Docker commands still require your approval. And your actual code (PHP, composer, wp-cli) runs fully sandboxed. Claude never sees your wp-config.php with all those database credentials.
You’re protecting where it matters most.
Scenario 3: Maximum Paranoia Mode (Untrusted Code)
Reviewing a pull request from an unknown contributor? Auditing a dependency after a security advisory? This is when you want full lockdown.
What this does: Every command prompts—even sandboxed ones. No escape hatch. Common data exfiltration tools (curl, wget, nc) are explicitly blocked. Three walls, all OS-enforced.
Malicious README contains hidden instructions to steal your AWS credentials? Claude literally cannot read ~/.aws/. The kernel says no. End of story.
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The YOLO Warning: Why This Actually Matters
Let me be direct with you for a second.
Running Claude Code without sandbox is genuinely risky. I’m not being dramatic—this is just the reality of how npm packages work.
Every npm package you install runs postinstall scripts with full access to your system. Every malicious prompt hidden in a README could trick Claude into reading your credentials. Every compromised dependency could phone home with your data.
“It probably won’t happen to me” is not a security strategy.
(It’s barely even a sentence.)
The Claude Code Sandbox isn’t paranoia. It’s basic hygiene. Like washing your hands. Like wearing a seatbelt. Like not storing passwords in a Google Doc called “passwords.txt.”
The 84% reduction in permission prompts? That’s nice. That’s a quality-of-life improvement. But the real win is protection that actually works—because it’s enforced at the kernel level, not just “Claude, please don’t do bad things.”
What Sandbox Doesn’t Protect
Let’s be honest about the limits, though. Sandbox protects your system files, SSH keys, AWS credentials, shell config, and network exfiltration.
It does not protect your project files from mistakes, defend against social engineering, or magically secure allowed domains.
The sandbox makes Claude safe to use autonomously. It doesn’t make you invincible.
👉 Use git. Review changes. Read prompts when they appear. (The ones that do appear now actually matter—which is kind of the whole point.)
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Stop Configuring, Start Building
Here’s the thing about sandbox configuration:
every project is different. Next.js needs different settings than Django. WordPress with Docker needs different settings than a Python CLI tool.
Figuring out the right config for YOUR specific codebase? That’s tedious. That’s the kind of thing that makes you put it off until “later” (which, let’s be honest, means “never”).
Analyzes your codebase — Detects your stack, package managers, frameworks, Docker usage, sensitive files
Asks smart questions — Only what it can’t figure out automatically
Generates your config — Tailored to YOUR project, ready to paste
No more reading documentation. No more guessing which domains you need. No more discovering your config is wrong when commands fail at the worst possible moment.
After adding the marketplace, the sandbox-architectskill will be available for installation and will help you configure sandbox settings for your projects.
That’s it.
Next time you start a project, just ask:
> Help me configure sandbox settings for this project
The Claude Code Sandbox isn’t just a feature—it’s a fundamental shift in how you work with AI coding assistants. Boundaries instead of babysitting. Protection that works because physics says so, not because we asked nicely.
What project are you going to secure first?
Drop a comment below—I’d love to hear what you’re building.
We’re staying in the SEO lane—updating meta titles, descriptions, focus keywords, image alt text, and Open Graph settings. You know. All the tedious stuff that makes SEO optimization feel like a part-time job nobody applied for.
To manage these settings, you need an SEO plugin. I’m using Rank Math.
Why Rank Math? Honestly? Because it’s what I use on my own site. No fancy reason—I’m showing you real projects I actually need. A bit of selfishness, sure. But that’s the deal I made with you.
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The Problem That’s Been Nagging Me
Here’s my situation. (And I bet—I really bet—you’re in the same boat.)
I’ve been publishing newsletters for 28 consecutive weeks now.
Twenty-eight weeks of hitting “publish” and hoping—really hoping—the SEO gods would smile upon me. Twenty-eight weeks of telling myself I’d go back and optimize everything “later.”
You know how that goes.
The whole time, I believed good content would naturally attract readers. And to some extent? That’s true. But optimizing for SEO amplifies everything.
Here’s the thing:
Since I never focused on SEO before, going back to optimize all those posts is a mountain of work. The kind of mountain that makes you want to lie down, stare at the ceiling, and pretend the problem doesn’t exist.
(Sound familiar?)
Sure, I could subscribe to Rank Math Premium and use their bulk edit feature.
But then WordPress 6.9 introduced the WordPress Abilities API.
And suddenly—suddenly—we can hook our WordPress sites directly to AI agents via MCP.
So here’s what I’m building: a Rank Math extension that exposes SEO functionality through the WordPress Abilities API. Mass updates. AI-powered. Hands-free. The workflow is nearly identical to the internal linking plugin I built before. A few tweaks here and there—specific adjustments for extending someone else’s plugin.
Let me walk you through it.
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Step 1: Brainstorming for Requirements
Every vibe coding project starts the same way for me: brainstorming requirements.
I use Claude web for this. Something about it works better for the back-and-forth Q&A sessions—the clarifying questions, the drilling down into what I actually want.
I start with a rough description of the plugin I need, then use my go-to prompt:
PROMPT: Requirements for WordPress Abilities API SEO Extension
The Rank math WordPress plugin doesn't have REST API. Instead of building our own REST API, I want to use the latest abilities API from WordPress to create abilities for the Rank Math WordPress plugin. We are not building it on top of the Rank Math plugin. This is a standalone plugin. However, it does need the Rank Math plugin in order for it to work.
The abilities I'm thinking of are:
- Search posts, custom post types, pages (default: post) by keywords, categories, tags, custom taxonomies, id, author, date range, etc
- get post, custom post type, page (default: post) by id. This would retrieve the full content of the post including title, content, excerpt, featured image, taxonomies, author info, as well as Rank Math SEO data like focus keyword, meta title, meta description, and any other relevant SEO fields that Rank Math manages for that post.
- update the rank math seo data for a given post, custom post type, or page by id. This would include updating fields like focus keyword, meta title, meta description, schema settings, social media metadata, and any other SEO-related fields that Rank Math handles.
The main Rank Math plugin is located at: /Users/nathanonn/LocalSites/abilities-api/app/public/wp-content/plugins/seo-by-rank-math
You can read the codebase to understand how the main Rank Math plugin works.
Please use the "wp-abilities-api" skill to help you with any WordPress Abilities API related tasks.
The idea is to create a separate plugin that exposes a REST API for interacting with Rank Math SEO data using LLM via MCP server.
I want you to help me brainstorm for the requirements of this plugin. Focus on business logic and rules, user stories, and acceptance criteria. No need to include technical implementation details.
The Rank math WordPress plugin doesn't have REST API. Instead of building our own REST API, I want to use the latest abilities API from WordPress to create abilities for the Rank Math WordPress plugin. We are not building it on top of the Rank Math plugin. This is a standalone plugin. However, it does need the Rank Math plugin in order for it to work.
The abilities I'm thinking of are:
- Search posts, custom post types, pages (default: post) by keywords, categories, tags, custom taxonomies, id, author, date range, etc
- get post, custom post type, page (default: post) by id. This would retrieve the full content of the post including title, content, excerpt, featured image, taxonomies, author info, as well as Rank Math SEO data like focus keyword, meta title, meta description, and any other relevant SEO fields that Rank Math manages for that post.
- update the rank math seo data for a given post, custom post type, or page by id. This would include updating fields like focus keyword, meta title, meta description, schema settings, social media metadata, and any other SEO-related fields that Rank Math handles.
The main Rank Math plugin is located at: /Users/nathanonn/LocalSites/abilities-api/app/public/wp-content/plugins/seo-by-rank-math
You can read the codebase to understand how the main Rank Math plugin works.
Please use the "wp-abilities-api" skill to help you with any WordPress Abilities API related tasks.
The idea is to create a separate plugin that exposes a REST API for interacting with Rank Math SEO data using LLM via MCP server.
I want you to help me brainstorm for the requirements of this plugin. Focus on business logic and rules, user stories, and acceptance criteria. No need to include technical implementation details.
A few rounds of Q&A later, Claude compiles the full requirements:
(I’m skipping the detailed brainstorming walkthrough this time. If you want the step-by-step breakdown, check my previous post—I covered the entire process there.)
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Step 2: Project Folder Setup
Nothing glamorous here—but necessary.
I set up the project folder and install the wp-abilities-api skill.
I also installed three additional skills (optional, but useful):
build-insights-logger: Captures insights during the build so Claude Code learns from the process and avoids repeating mistakes
skill-creator: Creates new skills on the fly if needed
mcp-builder: In case I need to spin up an MCP server quickly
After that, I dropped the requirements into the notes/ folder and created a blank main plugin file (wp-abilities-seo-extension.php).
Ready to build.
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Step 3: Build the Plugin with One Shot Prompt
Everything’s in place. Time to ask Claude Code to build the entire plugin.
One shot.
Yes, one prompt.
Sounds ambitious—maybe even reckless—but it works because the requirements are comprehensive and the wp-abilities-api skill handles the heavy lifting.
Here’s the exact prompt:
Based on the requirements at @notes/requirements.md, please help me build the plugin from scratch.
Please use the "wp-abilities-api" skill to help you with any WordPress Abilities API related tasks.
Please use the "build-insights-logger" skill to automatically log meaningful insights, discoveries, and decisions during coding session.
The main Rank Math plugin is located at: /Users/nathanonn/Studio/wp-test/wp-content/plugins/seo-by-rank-math
You can read the codebase to understand how the main Rank Math plugin works.
Short prompt.
No novel required.
Why? Because everything Claude needs lives in the requirements document and the skills. The only addition: the Rank Math plugin location. Claude needs to read and understand the codebase of the plugin we’re extending.
That’s the critical piece for building third-party extensions. Point Claude at the source code.
I’m using Claude Code in Plan Mode with Opus 4.5. This lets it explore, research, and strategize before writing a single line of code.
Claude fires up two explore agents in parallel:
One reads the project structure and requirements
One dives into the Rank Math codebase
Then it consults the wp-abilities-api skill to understand proper registration patterns:
At this point, Opus 4.5 has a complete picture:
The project state (empty plugin)
Rank Math’s meta keys and helper functions
WordPress Abilities API registration patterns
Time to plan.
The plan is comprehensive. Detailed architecture. Clear implementation phases. All thanks to Opus 4.5’s capabilities combined with thorough requirements.
I agreed to the plan. Implementation begins.
(The full build process is Claude generating codes while I drink coffee. Nothing riveting to watch.)
This is the part where I’d normally tell you to go make a sandwich.
But you won’t need to.
Less than 6 minutes later: Opus 4.5 completes the build.
Six minutes.
For a complete WordPress Abilities API plugin.
Stay with me here.
21 PHP files. Core infrastructure. Provider layer. Services. Error handling. All 10 abilities implemented.
Because I included the build-insights-logger skill in my prompt, Claude captured every key decision and discovery during development:
These insights become documentation.
Learning material for the next build.
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Step 4: Test the Plugin with Claude Code
Build complete.
But before we pop any champagne (or, you know, instant coffee)—we test.
Here’s my testing prompt:
Please activate & test out the plugin:
- Test all the abilities via REST API. Example endpoint:
`GET /wp-json/wp-abilities/v1/seo-abilities/get-seo-meta/run?input[post_id]=1`
- Verify that the MCP discovery shows all 10 abilities correctly.
- Test error handling by providing invalid post IDs and ensuring that the plugin responds appropriately.
Please use the "wp-abilities-api" skill to help you with any WordPress Abilities API related tasks.
Please use the "build-insights-logger" skill to automatically log meaningful insights, discoveries, and decisions during coding session.
You have access to WP-CLI commands to help you with the development and troubleshooting.
Three focus areas:
Test abilities via REST API
Verify MCP discovery shows all 10 abilities
Test error handling with invalid inputs
Claude runs through the tests:
(Again, nothing thrilling here. Claude does the work. I watch with my coffee.)
Test results come in:
All 10 abilities working. MCP discovery correct. Error handling validated.
The summary shows exactly what each ability does and any notable behaviors.
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Step 5: Use Test Results for Improvements
Tests passed.
But—and this is important—passing tests doesn’t mean perfect code.
I asked Opus 4.5 to analyze the test results and suggest improvements:
Based on your test results, identify the areas that may need improvement or further testing, and come up with a plan to address them.
Claude explores the codebase again, this time hunting for edge cases and potential issues:
It found several areas to improve:
Permission callback consistency
Image validation for orphaned images (HTML references to non-existent attachments)
Output schema enhancements
Claude even asked a clarifying question about handling orphaned images. (I chose the recommended option: add new fields to distinguish orphaned images while preserving the original reference ID for debugging.)
Improvements implemented:
The changes:
Permission Callbacks: Changed 7 abilities from check_edit_post_permission to check_edit_posts_permission for better error handling
Image Validation: Added attachment existence validation, new is_orphaned and referenced_id fields for orphaned images
Output Schema: Added images_orphaned count to the get_post_images return data
All verified with fresh tests. 29 orphaned images detected correctly on my site. The schema updates reflected in MCP discovery.
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Step 6: Put the Plugin to Work
Everything’s built and tested.
Now comes the fun part—actually using it.
The process mirrors what we did with the internal links plugin. First, install the MCP Adapter plugin into your WordPress site.
With the adapter active, I asked Claude what abilities my WordPress site has:
All 10 abilities visible. Three categories. Ready to go.
Now for the moment of truth—the reason I built this whole thing in the first place.
I asked Claude to optimize SEO for a specific post:
I want to optimize my post for SEO (ID: 1557). First, scan the post to understand its content and current SEO setup. Then, propose improvements that fall within your abilities.
Claude immediately starts gathering data. Multiple abilities firing in parallel:
Four abilities. One request. All the SEO data I need.
Here’s what Claude found—and honestly, it stings a little to share this:
The diagnosis:
SEO Score: 33/100 (Poor)
Title: 82 characters (max recommended: 60)
Description: 202 characters (max: 160)
Keyword in title: Missing
Social meta: Completely empty
Images: 3 total, 0 with alt text
Ouch.
But also? Exactly why I built this plugin.
Claude analyzed the issues and proposed a complete optimization plan:
The plan covers everything: shorter title with keyword, trimmed description, Facebook/Twitter metadata, and contextual alt text for all three images.
Expected result: SEO score from 33 → 80+.
I approved. Claude executed:
Interesting note: the bulk image update failed, so Claude adapted and updated each image individually. Problem-solving on the fly.
Results summary:
Metric
Before
After
SEO Title
82 chars (too long, no keyword)
58 chars ✅ with keyword
Meta Description
202 chars (too long, no keyword)
153 chars ✅ with keyword
Social Meta
Empty
Facebook & Twitter configured ✅
Images with Alt Text
0/3
3/3 ✅
All 5 SEO tests now pass. Previously: 1 pass, 3 warnings, 1 fail.
Let me verify in the WordPress admin:
SEO score: 71/100.
Not quite the 80+ the plan aimed for—but jumping from 33 to 71? I’ll take it.
Especially considering I did nothing except approve a plan.
The snippet preview shows proper character counts. Title at 59/60. Description at 152/160. Both in the green zone.
And the images:
All three images now have descriptive, contextual alt text. Claude understood what each image showed and wrote appropriate descriptions.
In under 6 minutes of build time, we created a WordPress plugin that:
Exposes 10 SEO abilities through the WordPress Abilities API
Integrates with Rank Math (with architecture ready for Yoast, AIOSEO, etc.)
Lets AI agents read, analyze, and update SEO settings
Handles bulk operations for mass optimization
Manages image alt text across your entire content library
The real unlock?
Your WordPress site now speaks MCP.
Any AI agent—Claude Code, custom bots, automation pipelines—can now optimize your SEO programmatically. No clicking through admin panels. No manual data entry. No tedious bulk editing. You describe what you want. The AI executes using the abilities you’ve exposed through the WordPress Abilities API.
This is the promise of WordPress 6.9’s Abilities API.
And we’re just scratching the surface.
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What’s Next?
Two plugins down. Both solving real problems I face on my own site.
The pattern works:
Brainstorm requirements with Claude
Set up project with the right skills
One-shot build with comprehensive prompt
Test and iterate
Deploy and use
For extending third-party plugins, add one step: point Claude at the source code.
Remember those 28 weeks of newsletters I mentioned at the start? The mountain of SEO work that made me want to lie down and stare at the ceiling?
It’s not a mountain anymore.
It’s a checklist. And I have an AI agent with a pen.
What tedious WordPress task are you going to automate next?
You know that thing where you’ve got 47 browser tabs open?
Not because you’re researching anything profound. No. You’re just trying to find that one post you wrote six months ago—the one about WooCommerce setup, or was it the product pages tutorial?—because you need to link to it from the article you’re publishing today.
Tab after tab after tab. Command+F. Scroll. Squint. Copy URL. Switch back. Find the right words to anchor. Paste. Format.
Thirty minutes later, you’ve added three internal links.
Three.
And honestly? They’re probably not even the best ones.
Here’s the thing: I’ve been that person. Staring at a perfectly good 2,000-word post with zero internal links, knowing full well that Google loves them, readers need them, and my inner SEO voice won’t shut up about it.
So I built something.
And what I discovered about WordPress 6.9’s new Abilities API might just change how you think about your entire site.
Stay with me.
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The Problem Nobody’s Actually Solving
Let’s be honest about what’s out there right now.
Manual linking eats 10-30 minutes per post. That’s not a workflow—that’s a hostage situation.
Keyword-based plugins spray links everywhere like a toddler with a garden hose. “AI” gets linked to “AirAsia.” I wish I were joking.
Regex matching sounds smart until it isn’t. It matches strings. It doesn’t understand meaning. Big difference.
Context blindness is the real killer. These tools can’t tell the difference between your Gutenberg tutorial and your post about WordPress editor basics—even though they’re obviously related.
The existing solutions are solving the wrong problem.
They’re trying to match strings when they should be understanding meaning.
And then WordPress 6.9 launched on December 2nd, 2025.
Buried in the release notes was something called the Abilities API. Most developers scrolled right past it.
I didn’t.
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The Discovery That Changed Everything
What happens when you combine WordPress’s new Abilities API with Claude Desktop and an MCP server?
Magic. Actual magic.
(Okay, not actual magic. But close enough that I did a little chair dance when it worked.)
Instead of regex patterns hunting for keywords, I created abilities that do something radical—they think.
Search posts semantically. When you write about “selling products online,” it finds your WooCommerce setup guide. Because it understands what you mean.
Analyze content context. It knows your Gutenberg blocks tutorial relates to your WordPress editor basics post. Not because of keywords. Because of meaning.
Add links intelligently. Places them where readers actually need them—not just where a keyword appears.
Validate links automatically. Checks if targets still exist. No more embarrassing 404s hiding in your archive.
The kicker?
AI decides where to place links based on actual content understanding.
Not keywords. Not patterns. Understanding.
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Building the Plugin: From Idea to Production
Here’s where it gets fun.
I’m going to walk you through exactly how I built this—from brainstorming to a working plugin with 9 abilities. The whole journey took about 3 hours.
(Three hours! To build something that would’ve taken weeks the traditional way. I’m still a little giddy about it.)
Phase 1: Getting Clear on What I Actually Wanted
I started in Claude Web with my wp-abilities-api skill loaded.
No documentation hunting. No API reference rabbit holes. Claude already knew the patterns.
PROMPT: Abilities API requirements brainstorming
I want to use the latest abilities API from WordPress to create abilities to add / update / remove internal links for posts.
The abilities I'm thinking of are:
- Search posts, custom post types, pages (default: post) by keywords, categories, tags, custom taxonomies, id, author, date range, etc
- get post, custom post type, page (default: post) by id. This would retrieve the full content of the post including title, content, excerpt, featured image, taxonomies, author info for that post.
- add / update / remove internal links in a post, custom post type, page (default: post) by id. This would involve specifying the source post id, target post id, anchor text, and link attributes (like nofollow, target blank, etc).
- validate internal links to ensure they point to existing posts, custom post types, or pages within the WordPress site.
- generate a report of all internal links within a specific post, custom post type, or page (default: post), including broken links, link attributes, and anchor texts.
Please use the "wp-abilities-api" skill to help you with any WordPress Abilities API related tasks.
The idea is to create a plugin that exposes a REST API for adding, updating, and removing internal links using LLM via MCP server.
I want you to help me brainstorm for the requirements of this plugin. Focus on business logic and rules, user stories, and acceptance criteria. No need to include technical implementation details.
I want to use the latest abilities API from WordPress to create abilities to add / update / remove internal links for posts.
The abilities I'm thinking of are:
- Search posts, custom post types, pages (default: post) by keywords, categories, tags, custom taxonomies, id, author, date range, etc
- get post, custom post type, page (default: post) by id. This would retrieve the full content of the post including title, content, excerpt, featured image, taxonomies, author info for that post.
- add / update / remove internal links in a post, custom post type, page (default: post) by id. This would involve specifying the source post id, target post id, anchor text, and link attributes (like nofollow, target blank, etc).
- validate internal links to ensure they point to existing posts, custom post types, or pages within the WordPress site.
- generate a report of all internal links within a specific post, custom post type, or page (default: post), including broken links, link attributes, and anchor texts.
Please use the "wp-abilities-api" skill to help you with any WordPress Abilities API related tasks.
The idea is to create a plugin that exposes a REST API for adding, updating, and removing internal links using LLM via MCP server.
I want you to help me brainstorm for the requirements of this plugin. Focus on business logic and rules, user stories, and acceptance criteria. No need to include technical implementation details.
My initial prompt was simple: I want to create abilities for managing internal links.
Claude came back with targeted questions. Not generic ones—targeted.
My answers to Claude’s questions:
Notice what’s happening here. Each answer shaped the architecture. No guessing. No over-engineering. No building features I’d never use.
After a few rounds, Claude produced a comprehensive requirements document:
The key architectural decisions that emerged:
LLM-First Design — All abilities optimized for AI consumption via MCP. Because that’s the whole point.
Editor-Aware — Handles Gutenberg blocks vs Classic Editor automatically. No more “works in one, breaks in the other.”
Permission-Based — Respects WordPress capabilities system. Because security isn’t optional.
Operation-Focused — The plugin handles CRUD operations. AI handles the intelligence. Clean separation.
Phase 2: Letting Claude Code Do the Heavy Lifting
With requirements locked, I opened VS Code and set up my workspace:
The setup was deliberate.
wp-abilities-api skill installed. Build-insights-logger to capture discoveries. Requirements document in the notes folder. Clean plugin directory ready to go.
Then I triggered Claude Code with plan mode:
PROMPT: Build Plugin From Scratch
Based on the requirements at @notes/requirements.md, please help me build the plugin from scratch.
Please use the "wp-abilities-api" skill to help you with any WordPress Abilities API related tasks.
Please use the "build-insights-logger" skill to automatically log meaningful insights, discoveries, and decisions during coding session.
You have access to WP-CLI commands to help you with the development.
Based on the requirements at @notes/requirements.md, please help me build the plugin from scratch.
Please use the "wp-abilities-api" skill to help you with any WordPress Abilities API related tasks.
Please use the "build-insights-logger" skill to automatically log meaningful insights, discoveries, and decisions during coding session.
You have access to WP-CLI commands to help you with the development.
Watch what happened next.
Claude Code immediately read the requirements document, explored the current plugin state, activated the wp-abilities-api skill automatically, and studied the API documentation patterns.
Then came clarifying questions.
Even Claude Code wanted to be sure:
Three critical decisions:
Autoloading: Composer PSR-4. The professional standard.
Implementation: All 9 abilities at once. Comprehensive from the start.
Testing: No unit tests initially. Faster iteration. (We can add tests later. Don’t @ me.)
The plan was complete. Nine abilities. Core services. Professional architecture.
And I hadn’t written a single line of code yet.
Phase 3: Watching the Build Happen
Here’s what fascinates me—Claude Code used WP-CLI to test in real-time:
Real post IDs. Real execution. Real validation.
Every ability got tested. No assumptions. No “it should work” moments.
Editor-aware — Properly handles Gutenberg blocks AND Classic Editor. Finally.
Permission-based — Uses WordPress capabilities (read, read_post, edit_post). Your site stays secure.
Post lock support — Respects WordPress post editing locks. No stepping on collaborators’ toes.
MCP-ready — All abilities exposed via mcp.publicapi=true. AI can actually use them.
REST API enabled — Available via REST endpoints for whatever else you dream up.
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The Real Test: Can AI Actually Use This?
The plugin was built. The abilities were registered.
But could AI actually use them?
Time to find out.
Setting Up the Bridge
First, I installed the MCP Adapter plugin. This brilliant piece of engineering transforms WordPress abilities into MCP tools that AI can trigger.
The setup took 2 minutes. Two.
When I opened Claude Code, it immediately detected the MCP server:
The Moment of Truth
I started simple: “What kind of abilities does my WordPress site have?”
Claude Code triggered the discover-abilities tool:
All 9 abilities. Ready. Waiting.
Autonomous Internal Linking in Action
I grabbed a post from my site—an article about Claude Skills with zero internal links.
Post ID: 1557.
I asked Claude Code to scan the post, search for related content, and add internal links.
Here’s what happened.
Step 1: Reading the post
Claude read the entire post. Understood it was about Claude Skills, design systems, and creating reusable components.
Step 2: Searching for relevant content
26 related posts found. But Claude didn’t just grab random matches.
Step 3: Intelligent link selection
Look at those choices:
“Claude Skills” → Links to Part 1 intro article
“Claude Code” → Links to tips article for tool mastery
“component library” → Connects to Part 3 about mastering libraries
“reusable forever” → Points to Part 2 about code reusability
Each link made semantic sense. No keyword stuffing. No forced matches. Just… relevance.
Step 4: Applying the links
One API call. Four links inserted.
The Results
I opened my post in the WordPress editor.
There they were:
The transformation:
Before: 0 internal links, isolated content
After: 4 contextually perfect internal links
Time taken: Less than 2 minutes
Human effort: One prompt
But here’s what really got me.
Claude understood that when I mentioned “component library” in the context of ShadCN UI, it should link to my article about mastering libraries in Claude Skills.
When I wrote “reusable forever” about turning code into superpowers, it linked to Part 2 of my Claude Skills series—which is literally about that exact topic.
No regex could do this. No keyword matching could understand this context.
This is what the WordPress Abilities API makes possible.
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What We Built (The Recap)
Let’s step back for a second:
Brainstormed requirements with Claude using the wp-abilities-api skill
Built the plugin with Claude Code in plan mode—9 abilities, full architecture
Connected via MCP to enable AI-powered internal linking
Tested with real content—AI understanding context and applying relevant links
The entire journey: 3 hours.
The result: A production-ready plugin that fundamentally changes how WordPress handles internal linking.
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Why This Actually Matters
Remember the old way?
Manual linking: 30 minutes to add 5-10 links
Keyword plugins: Spam with irrelevant matches
Zero context: No understanding of content meaning
Now?
AI-powered linking: Less than 2 minutes for contextually perfect links
Semantic understanding: Links based on actual meaning
Full automation: One prompt, complete results
The WordPress Abilities API combined with AI doesn’t just save time.
My accounting app was giving me existential dread.
Not because of the numbers.
(Well, okay, sometimes because of the numbers.)
But because every time I opened it, I felt like I was staring at the digital equivalent of beige wallpaper.
You know that feeling, right? When your app works perfectly but has all the personality of a doctor’s waiting room?
Mine tracked profit and loss beautifully. Managed transactions like a champ. Did everything an accounting app should do. It was built with ShadCN UI—that clean, functional, utterly forgettable component library that makes every SaaS tool look like it came from the same factory.
It was the IKEA furniture of web apps.
Gets the job done.
Zero personality.
(Sorry, IKEA. I still love your chicken wings.)
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Here’s the thing: I needed something that felt like mine.
Something with actual personality.
Something that made number-crunching feel less like detention and more like… well, still accounting, but prettier accounting. The kind where you actually want to open the app instead of avoiding it like that one friend who only calls when they need help moving.
That’s like deciding to repaint your house yourself.
Sounds doable until you’re standing there with a brush, realizing you need to paint Every. Single. Room. Every. Single. Wall. And somehow make them all match.
Unless…
(Stay with me here.)
What if you could redesign ONE room, capture that exact paint color and technique, then magically apply it everywhere else?
The Thing We Don’t Talk About: Generic Design Syndrome
Look familiar?
That screenshot is my accounting dashboard.
Could be yours. Could be literally anyone’s. It’s the starter home of SaaS designs—functional, affordable, and identical to every other one on the block.
It’s not bad.
It’s just… there.
Like elevator music. Like hotel art. Like those conversations where someone asks “how are you?” and you say “fine” even though you’re absolutely not fine because your app looks like it was designed by a committee of robots who’ve never felt joy.
(Too dramatic? Maybe. But you’re still reading, aren’t you?)
Here’s the choice every developer faces—and it’s a lousy choice:
Use a component library → Fast to build, looks like everyone else’s
Design from scratch → Unique, but requires the time commitment of a second mortgage
Hire a designer → Professional, costs more than your monthly coffee budget (and that’s saying something)
But wait.
There’s a door number four that nobody talks about.
What if you could create a design system once—just once—turn it into a Claude Skill, and apply it everywhere automatically?
Let me show you how.
(Spoiler: It takes less time than your last Zoom call.)
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Step 1: Let Claude Show You What’s Possible (5 Minutes)
I opened Claude Code and pointed it at my sad, slate dashboard.
The key move?
I used the frontend-design skill (you can download it from here) and asked for 5 completely different HTML variants.
Not tweaks. Not “make the blue slightly bluer.”
I wanted personality. Drama. Something that would make my accountant jealous.
(Do accountants get jealous of app designs? Let’s say yes.)
Claude Code immediately understood the assignment:
Look at these descriptions—each one a different personality:
Neo-Brutalist: Like your app went to art school and came back wearing all black
Glass Aurora: What happens when the Northern Lights become a UI (dreamy!)
Editorial Mono: The New Yorker meets your dashboard
Warm Minimal: Like a hygge hug for your data
Dark Command: For when you want to feel like you’re hacking the Matrix while doing expense reports
Five completely different vibes.
From one prompt.
It’s like speed-dating for design systems. (Is that a thing? It should be a thing.)
Each one broke free from that typical AI-generated aesthetic we all recognize. You know the one—like someone asked a robot to paint a sunset.
I fell hard for the Glass Aurora variant.
Yes, it had that slightly AI-ish glassmorphism thing happening.
But those aurora gradients?
Chef’s kiss.
It was like my dashboard went to Iceland and came back enlightened.
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Step 2: Make It Yours (2 Minutes of Pure Joy)
The Glass Aurora design only came in dark mode.
But I needed both themes because I’m one of those people who switches to light mode at 6 AM like a responsible adult.
(I switch back to dark mode by lunch. We all have our limits.)
Claude Code didn’t just invert the colors like a lazy Instagram filter:
Look at that attention to detail:
Soft gradients from slate to purple/teal (not harsh, not boring)
White glass panels with 60-75% opacity (visible but not overwhelming)
Pastel backgrounds that don’t burn your retinas
Subtle gradient borders for depth (the devil’s in the details, friend)
Perfect.
I had my design.
Now here’s where most people would start the tedious work of manually copying styles across 47 different components.
Don’t be most people.
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Step 3: Turn Your Design Into Documentation (10 Minutes That Save Your Life)
I switched to Claude Web (it’s better for this documentation dance) and attached both HTML files:
My request was specific.
(Specificity is your friend here. Vague requests get vague results. It’s like ordering “food” at a restaurant.)
PROMPT: Generate Complete Design System Documentation from HTML Files
I need you to analyze the attached HTML files and create two comprehensive design system documents:
### Document 1: Complete Design Guidelines (Markdown)
### Document 2: Interactive Reference Style Guide (HTML)
## Requirements for Both Documents
### Analysis Phase
First, thoroughly analyze ALL attached HTML files to extract:
1. **All CSS variables and design tokens** (colors, spacing, shadows, radius, etc.)
2. **All typography patterns** (font families, sizes, weights, line heights)
3. **All component patterns** (buttons, cards, forms, navigation, etc.)
4. **All layout patterns** (grids, containers, multi-column layouts)
5. **All utility classes** (margins, padding, text alignment, colors)
6. **All interaction patterns** (hover states, transitions, animations)
7. **Responsive breakpoints and mobile patterns**
8. **Naming conventions and prefixes used**
---
## Document 1: Design Guidelines (Markdown)
Create a comprehensive markdown file named `design-guidelines-complete.md` that includes:
### 1. Introduction Section
- **Design Philosophy**: Extract and articulate the design principles evident in the HTML
- **Key Characteristics**: What makes this design system unique
- **When to Use**: Guidance on appropriate use cases
### 2. Design Tokens
Complete CSS variable documentation with:
```css
:root {
/* Extract ALL CSS variables from the HTML files */
/* Group by category: colors, spacing, radius, shadows, etc. */
/* Include comments describing each token */
}
```
### 3. Typography System
- Font family stack
- Complete typography scale table with:
- Element/Use Case
- Font Size
- Font Weight
- Color
- Line Height
- Typography utility classes with code examples
### 4. Component Classes
Document EVERY component found in the HTML files with:
- Class name and purpose
- Complete CSS code
- Variants (if applicable)
- Usage notes
Organize by category:
- **Layout** (containers, grids, columns)
- **Cards** (all card variations)
- **Buttons** (all button types and states)
- **Forms** (inputs, textareas, selects, labels, file uploads)
- **Navigation** (navbar, links, menus)
- **Content Components** (articles, lists, chat bubbles, etc.)
- **UI Elements** (badges, tags, status indicators)
- **Specialized Components** (search bars, CTAs, heroes, sidebars)
### 5. Utility Classes
Complete list of utility classes for:
- Spacing (margins, padding)
- Typography (alignment, colors, weights)
- Display (flex, grid)
- Visibility
- Other utilities
### 6. Responsive Design
- Breakpoints used
- Mobile-first patterns
- Responsive grid behaviors
- Mobile-specific overrides
### 7. Animation & Transitions
- Timing functions
- Duration standards
- Transition patterns for different element types
### 8. Usage Examples
For each major component type, provide:
- Clean, minimal HTML example
- Real-world usage scenario
- Multiple examples showing variants
### 9. Accessibility Guidelines
- Color contrast requirements
- Focus states
- Semantic HTML recommendations
- Keyboard navigation notes
- ARIA considerations
### 10. Best Practices
- Implementation guidelines
- Common patterns
- Things to avoid
- Performance considerations
### 11. Additional Sections (if relevant)
- Color usage guidelines
- Icon/emoji usage
- Spacing scale
- Shadow elevation system
---
## Document 2: Reference Style Guide (HTML)
Create a comprehensive, interactive HTML file named `reference-styleguide-complete.html` that includes:
### Structure Requirements
1. **Self-Contained**: All CSS inline in a `<style>` tag
2. **Complete Design Tokens**: Include ALL CSS variables extracted from source files
3. **Live Examples**: Working, interactive examples of every component
4. **Organized Sections**: Clear sections with headers for each component category
### Required Sections
#### Header/Navigation
- Working navigation example from the source files
#### Color Palette Section
- Visual swatches for all colors
- Hex codes displayed
- Color names/variable names
- Organized by category (primary, secondary, neutrals, etc.)
#### Typography Section
- Live examples of every heading level
- Body text examples
- All typography variants demonstrated
- Labels, captions, meta text
#### Button Section
Demonstrate:
- All button variants (primary, secondary, outline, etc.)
- All sizes (small, medium, large)
- All states (normal, hover-able)
- Special buttons (pill, block, icon buttons)
- Button groups (if applicable)
#### Card Section
Show examples of:
- Basic cards
- Card variants (large, compact, etc.)
- Category cards
- Interactive cards with hover states
- Cards in grid layouts
#### Form Section
Include working examples of:
- Text inputs
- Textareas
- Select dropdowns (with custom styling)
- Checkboxes and radios (if in source)
- File uploads
- Input groups
- Form validation states (if applicable)
- Complete form layout example
#### Layout Section
Demonstrate:
- Container widths
- Grid systems
- Multi-column layouts
- Responsive behavior examples
#### Component Sections
For EVERY component found in source files, create a demo section:
- Search bars
- Navigation menus
- Article lists
- Chat interfaces
- Status badges
- Tabs/Pills (if applicable)
- Modals/Dialogs (if applicable)
- Tables (if applicable)
- Pagination (if applicable)
- Breadcrumbs (if applicable)
- And any other unique components
#### Utility Classes Section
Demonstrate utility classes with before/after examples
### Styling for the Style Guide Itself
Create a clean, professional layout for the style guide:
```css
.demo-section {
/* Section container styling */
}
.demo-header {
/* Section header styling - make it distinctive */
}
.demo-content {
/* Content area styling */
}
.color-swatch {
/* Color display boxes */
}
```
### Footer
- Notes about class prefixes
- Link to design guidelines
- Version information (if applicable)
---
## Output Format
Provide both files as downloadable outputs:
1. `/mnt/user-data/outputs/design-guidelines-complete.md`
2. `/mnt/user-data/outputs/reference-styleguide-complete.html`
---
## Quality Checklist
Before completing, ensure:
### Design Guidelines (MD)
- [ ] All CSS variables extracted and documented
- [ ] Every component class has complete CSS code
- [ ] At least 3-5 usage examples per major component
- [ ] Typography scale is complete with all variants
- [ ] Responsive patterns documented
- [ ] Accessibility guidelines included
- [ ] Best practices section is actionable
### Reference Style Guide (HTML)
- [ ] File opens and displays correctly in browser
- [ ] All colors displayed with swatches and codes
- [ ] Every component from source files is demonstrated
- [ ] Interactive elements work (hover states visible)
- [ ] Forms are functional (inputs accept text, etc.)
- [ ] Layout is clean and organized
- [ ] Sections are clearly labeled
- [ ] Self-contained (no external dependencies)
---
## Additional Instructions
1. **Be Thorough**: Don't skip any components, even small ones
2. **Extract Patterns**: If you see a pattern repeated, create a documented component for it
3. **Maintain Consistency**: Use the same class naming conventions from the source
4. **Provide Context**: Explain WHEN and WHY to use each component
5. **Think Developer-First**: Make it easy to copy-paste and implement
6. **Include Edge Cases**: Show how components look with long text, empty states, etc.
---
## Example Usage
After receiving these documents, a developer should be able to:
1. Understand the entire design system philosophy
2. Find any component they need with working code
3. Copy-paste implementation examples
4. See visual examples of every component
5. Understand responsive behavior
6. Know accessibility requirements
7. Follow best practices for implementation
---
Begin by analyzing all attached HTML files, then create both comprehensive documents.
I need you to analyze the attached HTML files and create two comprehensive design system documents:
### Document 1: Complete Design Guidelines (Markdown)
### Document 2: Interactive Reference Style Guide (HTML)
## Requirements for Both Documents
### Analysis Phase
First, thoroughly analyze ALL attached HTML files to extract:
1. **All CSS variables and design tokens** (colors, spacing, shadows, radius, etc.)
2. **All typography patterns** (font families, sizes, weights, line heights)
3. **All component patterns** (buttons, cards, forms, navigation, etc.)
4. **All layout patterns** (grids, containers, multi-column layouts)
5. **All utility classes** (margins, padding, text alignment, colors)
6. **All interaction patterns** (hover states, transitions, animations)
7. **Responsive breakpoints and mobile patterns**
8. **Naming conventions and prefixes used**
---
## Document 1: Design Guidelines (Markdown)
Create a comprehensive markdown file named `design-guidelines-complete.md` that includes:
### 1. Introduction Section
- **Design Philosophy**: Extract and articulate the design principles evident in the HTML
- **Key Characteristics**: What makes this design system unique
- **When to Use**: Guidance on appropriate use cases
### 2. Design Tokens
Complete CSS variable documentation with:
```css
:root {
/* Extract ALL CSS variables from the HTML files */
/* Group by category: colors, spacing, radius, shadows, etc. */
/* Include comments describing each token */
}
```
### 3. Typography System
- Font family stack
- Complete typography scale table with:
- Element/Use Case
- Font Size
- Font Weight
- Color
- Line Height
- Typography utility classes with code examples
### 4. Component Classes
Document EVERY component found in the HTML files with:
- Class name and purpose
- Complete CSS code
- Variants (if applicable)
- Usage notes
Organize by category:
- **Layout** (containers, grids, columns)
- **Cards** (all card variations)
- **Buttons** (all button types and states)
- **Forms** (inputs, textareas, selects, labels, file uploads)
- **Navigation** (navbar, links, menus)
- **Content Components** (articles, lists, chat bubbles, etc.)
- **UI Elements** (badges, tags, status indicators)
- **Specialized Components** (search bars, CTAs, heroes, sidebars)
### 5. Utility Classes
Complete list of utility classes for:
- Spacing (margins, padding)
- Typography (alignment, colors, weights)
- Display (flex, grid)
- Visibility
- Other utilities
### 6. Responsive Design
- Breakpoints used
- Mobile-first patterns
- Responsive grid behaviors
- Mobile-specific overrides
### 7. Animation & Transitions
- Timing functions
- Duration standards
- Transition patterns for different element types
### 8. Usage Examples
For each major component type, provide:
- Clean, minimal HTML example
- Real-world usage scenario
- Multiple examples showing variants
### 9. Accessibility Guidelines
- Color contrast requirements
- Focus states
- Semantic HTML recommendations
- Keyboard navigation notes
- ARIA considerations
### 10. Best Practices
- Implementation guidelines
- Common patterns
- Things to avoid
- Performance considerations
### 11. Additional Sections (if relevant)
- Color usage guidelines
- Icon/emoji usage
- Spacing scale
- Shadow elevation system
---
## Document 2: Reference Style Guide (HTML)
Create a comprehensive, interactive HTML file named `reference-styleguide-complete.html` that includes:
### Structure Requirements
1. **Self-Contained**: All CSS inline in a `<style>` tag
2. **Complete Design Tokens**: Include ALL CSS variables extracted from source files
3. **Live Examples**: Working, interactive examples of every component
4. **Organized Sections**: Clear sections with headers for each component category
### Required Sections
#### Header/Navigation
- Working navigation example from the source files
#### Color Palette Section
- Visual swatches for all colors
- Hex codes displayed
- Color names/variable names
- Organized by category (primary, secondary, neutrals, etc.)
#### Typography Section
- Live examples of every heading level
- Body text examples
- All typography variants demonstrated
- Labels, captions, meta text
#### Button Section
Demonstrate:
- All button variants (primary, secondary, outline, etc.)
- All sizes (small, medium, large)
- All states (normal, hover-able)
- Special buttons (pill, block, icon buttons)
- Button groups (if applicable)
#### Card Section
Show examples of:
- Basic cards
- Card variants (large, compact, etc.)
- Category cards
- Interactive cards with hover states
- Cards in grid layouts
#### Form Section
Include working examples of:
- Text inputs
- Textareas
- Select dropdowns (with custom styling)
- Checkboxes and radios (if in source)
- File uploads
- Input groups
- Form validation states (if applicable)
- Complete form layout example
#### Layout Section
Demonstrate:
- Container widths
- Grid systems
- Multi-column layouts
- Responsive behavior examples
#### Component Sections
For EVERY component found in source files, create a demo section:
- Search bars
- Navigation menus
- Article lists
- Chat interfaces
- Status badges
- Tabs/Pills (if applicable)
- Modals/Dialogs (if applicable)
- Tables (if applicable)
- Pagination (if applicable)
- Breadcrumbs (if applicable)
- And any other unique components
#### Utility Classes Section
Demonstrate utility classes with before/after examples
### Styling for the Style Guide Itself
Create a clean, professional layout for the style guide:
```css
.demo-section {
/* Section container styling */
}
.demo-header {
/* Section header styling - make it distinctive */
}
.demo-content {
/* Content area styling */
}
.color-swatch {
/* Color display boxes */
}
```
### Footer
- Notes about class prefixes
- Link to design guidelines
- Version information (if applicable)
---
## Output Format
Provide both files as downloadable outputs:
1. `/mnt/user-data/outputs/design-guidelines-complete.md`
2. `/mnt/user-data/outputs/reference-styleguide-complete.html`
---
## Quality Checklist
Before completing, ensure:
### Design Guidelines (MD)
- [ ] All CSS variables extracted and documented
- [ ] Every component class has complete CSS code
- [ ] At least 3-5 usage examples per major component
- [ ] Typography scale is complete with all variants
- [ ] Responsive patterns documented
- [ ] Accessibility guidelines included
- [ ] Best practices section is actionable
### Reference Style Guide (HTML)
- [ ] File opens and displays correctly in browser
- [ ] All colors displayed with swatches and codes
- [ ] Every component from source files is demonstrated
- [ ] Interactive elements work (hover states visible)
- [ ] Forms are functional (inputs accept text, etc.)
- [ ] Layout is clean and organized
- [ ] Sections are clearly labeled
- [ ] Self-contained (no external dependencies)
---
## Additional Instructions
1. **Be Thorough**: Don't skip any components, even small ones
2. **Extract Patterns**: If you see a pattern repeated, create a documented component for it
3. **Maintain Consistency**: Use the same class naming conventions from the source
4. **Provide Context**: Explain WHEN and WHY to use each component
5. **Think Developer-First**: Make it easy to copy-paste and implement
6. **Include Edge Cases**: Show how components look with long text, empty states, etc.
---
## Example Usage
After receiving these documents, a developer should be able to:
1. Understand the entire design system philosophy
2. Find any component they need with working code
3. Copy-paste implementation examples
4. See visual examples of every component
5. Understand responsive behavior
6. Know accessibility requirements
7. Follow best practices for implementation
---
Begin by analyzing all attached HTML files, then create both comprehensive documents.
Claude didn’t just list colors and fonts like a paint chip catalog.
It created a complete design philosophy:
Look at that structure—it’s like a love letter to your future self:
Find a bug in the glass effect? Fix it once in the skill. Every project gets the update.
Want to add a new component pattern? Update the skill. It’s everywhere instantly.
Need to onboard a developer? Share the skill. They’re designing consistently from minute one.
Every improvement compounds.
It’s like investing in index funds, but for your design system. (That’s the most adult sentence I’ve ever written. I need to go lie down.)
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The Benefits Nobody Mentions at Parties
Benefit #1: Design Consistency Without The Design Drama
You get enterprise-level design consistency without:
Figma (and its 47 comments per component)
Storybook (and its 3-hour setup process)
A design team (and their strong opinions about kerning)
Just you, your skill, and perfect consistency.
It’s beautiful.
Benefit #2: Instant Design Language That Actually Makes Sense
That 300-line SKILL.md?
It’s not just documentation. It’s your design philosophy, your patterns, your principles—all captured automatically.
It’s like having a tiny design consultant living in your codebase, but one that never sends invoices.
Benefit #3: Version Control for Visual Design
Your design system is now code. Which means:
Git trackable (see what changed and when)
PR reviewable (catch issues before they ship)
Rollback-able (when that neon green seemed like a good idea at 3 AM)
It’s version control for visuals.
The future is now, friend.
Benefit #4: Team Scalability Without the Scaling Pains
New developer joins the team?
Old way: “Here’s our 47-page design guide. Good luck!”
New way: “Use the sololedger-glass-aurora skill.”
Done.
They’re designing consistently from day one.
No training montage required.
Benefit #5: Professional Client Deliverables
That skill package? It’s also professional documentation you can hand to clients.
“Here’s our complete design system.”
Hands over ZIP file
Client is impressed
You look like a genius
(You ARE a genius, but now you have proof.)
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Your Turn: From Generic to Gorgeous in 30 Minutes
Ready?
Here’s your recipe for design transformation:
Step 1: Pick Your Victim (I mean, page)
Don’t try to redesign everything at once. (That way lies madness.)
Start with one page. Dashboard, landing page, settings—doesn’t matter.
Pick the one that makes you saddest.
Step 2: Generate Your Options
Use Claude Code with the frontend-design skill. Ask for 5 variants.
Be specific about the vibe you want. “Make it pretty” is not specific. “Make it look like Spotify met a disco ball at a Nordic design conference” is specific.
(Also intriguing.)
Step 3: Fall in Love (Then Refine)
Choose your favorite. Get both theme versions. Make sure it sparks joy. (Yes, I’m Marie Kondo-ing your design system. Deal with it.)
Step 4: Birth Your Skill
Switch to Claude Web. Attach the HTML files. Generate comprehensive documentation. Package with skill-creator.
Watch your design system become immortal.
Step 5: Deploy Your Beauty Everywhere
Add to your project. Use the skill to redesign everything.
Feel that? That’s the satisfaction of consistency. It’s better than finding matching socks.
Step 6: Make It Better (Forever)
Your skill isn’t frozen in carbonite. Improve it. Expand it. Share it.
Every enhancement makes every project better.
It’s compound interest for your eyeballs.
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The Real Talk Conclusion
I spent years accepting generic designs.
Not because I liked them.
But because custom design seemed too expensive—not in money, but in time.
Time I didn’t have.
Energy I couldn’t spare.
Mental bandwidth already allocated to remembering my passwords.
But what if custom design took 30 minutes instead of 30 days?
What if consistency was automatic instead of aspirational?
What if your design system could teach itself to any AI that needed it?
That’s not the future, friend. That’s what I just showed you.
My accounting app no longer looks like everyone else’s. It has personality. It has presence. It has that glass aurora glow that makes even tax calculations feel slightly magical. (Slightly. Let’s not get carried away—they’re still tax calculations.)
And it took less time than watching a Netflix episode.
(A short one. Not one of those prestige drama episodes that’s basically a movie.)
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Here’s My Challenge to You
Open that project with the generic UI. You know the one. The one you show people quickly while saying “it’s still in beta.”
Give it 30 minutes. Just 30.
Generate your variants. Pick your favorite. Make it a skill.
Watch as your entire app transforms from “functional” to “fascinating.”
Because life’s too short for boring dashboards, friend.
And your apps deserve to be as unique as you are.
(Even if you’re not that unique. I’m kidding! You’re totally unique. Your mother was right.)
What design will you capture as a Claude Skill today?
Go. Create. Make the internet prettier.
We’re all counting on you.
(No pressure.)
P.S. – That glass aurora design I fell in love with? I’ve now applied it to three different projects. Same skill. Same consistency. Same “ooh, what’s that?” reaction from everyone who sees it. Total time to redesign all three: under an hour. The old way would have taken weeks, and they all would have looked slightly different, like siblings who don’t quite look related.
P.P.S. – Want to create your own design skills but feeling overwhelmed? Start here: Download the frontend-design skill from GitHub. Ask for design variants. Pick your favorite. Watch the magic happen. Then write me a thank-you note. Or don’t. I’ll just be here, admiring my glass aurora dashboard and feeling quietly superior to everyone still using default Bootstrap.
P.P.P.S. – Yes, I know that’s too many P.S.’s. But you’re still reading, aren’t you? See? Sometimes breaking the rules works. Just like breaking free from generic design. Full circle, friend. Full. Circle.
That same gnarly issue that made you question your entire career choice last Tuesday. And the Tuesday before that. Your brain does that thing where it whispers: “Wait… didn’t I fix this already?”
You definitely fixed this already.
The solution exists somewhere—buried in a three-week-old Slack thread, or maybe that commit message you wrote at 2 AM when you were feeling particularly verbose. (Spoiler: You weren’t. The message says “fixed bug.”)
Here’s the thing: We’re hemorrhaging wisdom every single day.
Not because we’re not learning. We learn constantly. We discover edge cases, make architectural decisions, stumble upon performance tricks that would make your CS professor weep with joy.
But then? We move on. Next feature. Next sprint. Next fire.
And all that hard-won knowledge?
Poof.
Gone like your willpower at 3 PM when someone mentions there’s leftover birthday cake in the break room.
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The Problem: Claude Code Has The Memory of a Goldfish
Picture this: You’re vibe coding with Claude Code. (Yes, that’s a technical term now. Roll with it.)
Together, you and Claude are making dozens of micro-decisions every session:
“Oh right, this package completely changed its API in v2”
“We need to store files in org-scoped directories for multi-tenancy”
“This approach is 10x faster than the obvious solution”
“Never—and I mean NEVER—use pattern X here because of edge case Y”
These aren’t just code comments, friend. This is architectural wisdom. The kind that separates the “I can center a div” developers from the “I’ve seen things you wouldn’t believe” architects.
But here’s what happens next. (You already know where this is going, don’t you?)
Claude Code discovers something important
You fix the issue together
You high-five virtually and move on
Next week, Claude Code makes the exact. Same. Mistake.
You debug the exact. Same. Issue.
Rinse, repeat, cry a little
Sure, we’ve got CLAUDE.md for project rules.
But let me ask you something: When was the last time you updated that file after a coding session?
Cricket sounds.
Exactly.
Nobody has time to document discoveries when you’re in the zone. Nobody.
So I built a Claude Skill that remembers everything for us.
The Build Insights Logger skill creates what I like to call a “knowledge management system.” (Fancy, right? It’s actually pretty simple.)
Step 1: Automatic Capture – Logs insights while you’re coding
Step 2: Smart Review – Shows you insights organized by category
Step 3: Selective Integration – Adds the good stuff to CLAUDE.md
Step 4: Compound Learning – Every future session gets smarter
Let me show you how this saved my bacon. (Actually, it was more like saving me from a dependency nightmare, but “saved my bacon” sounds more dramatic.)
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Step 1: Automatic Knowledge Capture (While You Code!)
Here’s what the Build Insights Logger does brilliantly: it automatically logs meaningful insights as Claude Code works.
No manual documentation. No “I’ll add this to the docs later.” (You won’t.) No lost learnings.
Just automatic capture of:
Non-trivial edge cases you stumble upon
Design decisions and their rationale (the WHY behind the WHAT)
Performance optimizations that made you go “whoa”
Security implications that could bite you later
Architecture patterns you actually adopt
API gotchas and their fixes
Implementation trade-offs
Everything gets logged to .claude/insights/ during your session. Ready for review when YOU’RE ready.
Real-World Example: Building a Document Management System
On Monday, I was building a document management system. The complex kind—file uploads, multi-tenant storage, previews, the whole enchilada.
I started with my standard instruction to Claude Code
Notice the magic phrase: “Please use the build-insights-logger skill.”
That’s it. That’s all it takes.
Claude Code immediately gets it:
With the skill activated, Claude Code starts building. But—and here’s where it gets interesting—it’s not just coding. It’s documenting its discoveries:
As Claude works through the implementation, it automatically creates an insights log:
What Gets Captured: Real Architectural Decisions
These insights aren’t fluff. They’re the real deal—architectural decisions that matter:
Look at that first insight—a pluggable storage abstraction. Claude Code discovered you needed to support multiple storage backends (local disk, S3, Azure Blob) and documented the pattern.
Key insight captured: “By storing files in org-scoped directories with year/month structure (storage/documents/{orgId}/{yyyy}/{mm}/{filename}), we maintain tenant isolation at the filesystem level and enable efficient cleanup/archiving strategies.”
That’s not a code comment, friend.
That’s institutional knowledge.
As development continues, more insights accumulate:
Notice the categories:
Architecture: System design decisions
UI Patterns: Implementation approaches that actually work
Navigation: Integration strategies
Implementation Strategy: Why we’re building it this way
Each insight includes:
The files involved
Relevant tags (for finding it later)
Clear explanation of the decision
Why it matters (the part everyone forgets to document)
The Moment That Made Me a Believer: The cuid2 Bug
Here’s where the skill earned its keep.
After implementing the core functionality, I hit an error:
The build was failing. The error message? Cryptic as a fortune cookie: “Export cuid doesn’t exist in target module.”
Now, normally this triggers The Debugging Dance. You know the one—check imports, read docs, sacrifice a rubber duck to the Stack Overflow gods.
But watch what happened when I asked Claude Code to fix it and log the insight:
Claude Code didn’t just fix the bug.
It:
Researched the root cause
Created a comprehensive fix plan
Documented the gotcha for future reference
The fix was simple—the package had changed its API between v1 and v2:
But here’s the crucial part—this knowledge was captured permanently:
Look at that bug fix documentation:
Clear problem statement
Root cause analysis
Wrong pattern marked (with a big ❌)
Correct pattern provided (with a reassuring ✅)
Package version context
This bug will never bite us again.
Never.
(Well, unless we forget to use the skill. But we won’t. Right?)
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Step 2: Transforming Raw Insights Into Permanent Knowledge
So you’ve been capturing insights automatically. Your .claude/insights/ folder is filling up with valuable learnings like a wisdom piñata.
But insights in session files are like vegetables in your crisper drawer—valuable, but not helping anyone if they’re just sitting there.
Time for the review workflow. This is where the magic happens.
Triggering the Review: On YOUR Schedule
The Build Insights Logger respects your flow. It never interrupts with “Hey! Want to review your insights? How about now? Now? What about now?”
Never.
You review when YOU want. After the feature ships. After the bug is squashed. After your coffee. (Definitely after coffee.)
Here’s how simple it is:
One command: “Please use the build-insights-logger skill to review the insights from existing sessions.”
Claude Code immediately understands:
Watch what happens next. Claude doesn’t just dump a wall of text like your cousin’s Facebook posts. It systematically explores your insights directory:
Two session files found. 160 lines of insights total.
Raw knowledge waiting to be refined. Like coffee beans waiting to become that sweet, sweet nectar of productivity.
The Presentation: Organized, Categorized, Actually Useful
This is where the skill really shines.
Instead of showing you raw session logs (boring), Claude Code presents your insights like a senior architect presenting findings to the team:
Look at that organization!
Architecture & Design Patterns
Document storage abstraction with migration paths
Backend-first implementation strategy
Prisma & Database Patterns
Complex filtering with OR/AND combinations
Many-to-many relations with soft deletes
Each insight is:
Numbered for easy selection (1/, 2/, 3/…)
Categorized for context (because context is everything)
Summarized with key details
Explained with why it matters
The presentation continues:
Security & Permissions
Tiered permission levels for different operations
Defensive soft-delete checking
Data Integrity & Business Logic
Transaction links removed on soft delete
Per-file error handling in batch operations
And more:
UI Implementation Patterns
File upload with hidden input ref pattern
Document preview with MIME-type detection
Two-level navigation integration
Bug Fixes & Dependencies
That @paralleldrive/cuid2 import issue (remember that little rascal?)
13 insights total. Each one a potential bug prevented, a pattern established, a decision documented.
It’s like having a time machine that lets you send wisdom to your future self.
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Step 3: Curating Your Knowledge Base (Be Picky!)
Claude asks: “Which insights would you like to add to CLAUDE.md?”
This is where you become the curator of your own knowledge museum. (Fancy!)
3 & 4 – Prisma patterns (made generic for any schema)
5 – Tiered permissions (security pattern)
13 – The cuid2 import bug (never. again.)
Notice what I did with insight 3? “Make this rule generic so that it can be applicable for any Prisma schema.”
The skill doesn’t just copy-paste like a lazy intern. It adapts insights to be broadly useful.
I didn’t select everything. Some insights were too specific. Others were already covered.
Quality beats quantity.
Every. Single. Time.
The Integration: Surgical Precision (No Mess)
Watch what happens when Claude Code integrates my selected insights:
Claude reads my existing CLAUDE.md (278 lines) and begins surgical integration.
It doesn’t just slap new stuff at the end like a P.S. on a love letter. It finds the RIGHT sections:
The Permission Layers section gets enhanced with the tiered strategy:
GET endpoints for regular members
PATCH/POST/DELETE for destructive operations require admin
Clear examples with specific routes
A new Prisma Query Patterns section appears with that complex OR/AND filtering pattern:
// When combining multiple OR conditions in a single query, wrap them in AND:
if (where.OR) {
where.AND = [{ OR: where.OR }, { OR: searchConditions }];
delete where.OR;
}
This pattern will save you hours of debugging Prisma query conflicts.
Hours.
The Common Pitfalls section gets the cuid2 import pattern:
// ❌ WRONG - v1 pattern, will fail with "Export cuid doesn't exist"
import { cuid } from '@paralleldrive/cuid2';
// ✅ CORRECT - v2 exports createId
import { createId } from '@paralleldrive/cuid2';
Complete with root cause explanation. This bug will never happen again in any project.
The insights aren’t lost. They’re archived. But the valuable patterns? They’re now in CLAUDE.md where they’ll guide every future coding session.
It’s like upgrading from sticky notes to a proper filing system. (But one that actually works.)
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The Selection Philosophy: What Makes the Cut?
Not every insight belongs in CLAUDE.md.
Here’s my selection criteria. (Yes, I have criteria. I’m fancy like that.)
Always Include:
Universal patterns that apply across features
Security decisions that affect the whole app
Performance optimizations that should be standard
Bug fixes for external dependencies
Architectural principles that guide development
Usually Skip:
Feature-specific implementation details
One-off workarounds
Obvious patterns Claude already knows
Project-specific business logic
Temporary fixes waiting for upstream patches
Transform When Adding:
Make patterns generic (not tied to specific models)
Extract the principle, not just the implementation
Add context about when to apply (and when NOT to)
Include examples that clarify usage
The goal isn’t to document everything. The goal is to capture patterns that make your next project better.
Less encyclopedia, more greatest hits album.
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The Compound Effect:
Here’s what happens over time. (Spoiler: It’s beautiful.)
Week 1: You capture 10 insights about authentication patterns
Week 2: You capture 8 insights about performance optimizations
Week 3: You capture 12 insights about error handling
Month 2: You have 100+ insights spanning every aspect of your codebase
Now imagine Claude Code with access to all of that institutional knowledge.
It’s not just avoiding bugs. It’s:
Consistent architectural decisions
Proven patterns applied automatically
Edge cases handled proactively
Performance optimizations baked in
Security considerations from day one
Your codebase doesn’t just grow. It evolves.
(Like Pokémon, but for code.)
Picture this:
Before this review:
2 session files with 13 insights
Knowledge trapped in temporary logs
Claude Code blissfully unaware
After 2 minutes of review:
5 critical patterns added to permanent knowledge
CLAUDE.md enhanced with battle-tested wisdom
Every future session benefits
Now multiply this across every coding session:
Week 1: 5 insights added → Next development avoids 5 issues
Week 2: 8 more insights → Next development avoids 13 issues
Month 2: 50+ insights → Your codebase is basically bulletproof
Each review session doesn’t just improve documentation. It improves every future line of code Claude writes.
It’s compound interest for your codebase.
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Your Complete Workflow: From Chaos to Compound Knowledge
Here’s your complete workflow. (Print this out. Stick it on your monitor. Tattoo it on your forearm. Whatever works.)
During Development (Automatic):
Activate build-insights-logger at session start
Code normally—insights log automatically
Discoveries, decisions, and fixes are captured
Session file grows with valuable learnings
After Development (5 minutes):
Request review: “Review insights from existing sessions”
Read through categorized insights
Select the valuable patterns (usually 30-50%)
Let Claude integrate into CLAUDE.md
Session files archive automatically
Next Development (Automatic Benefits):
Claude reads enhanced CLAUDE.md
Applies all captured patterns
Avoids all documented pitfalls
Implements proven architectures
Your code is better without trying
It’s not just documentation.
It’s evolutionary development.
Each development builds on the learnings of the last. Like standing on the shoulders of giants, except the giant is your past self. (Your past self is very tall in this metaphor. Roll with it.)
You’ve just discovered this game-changing AI Elements library—launched recently, perfect for what you need. Your brain is doing that excited thing where it’s already building the feature before your fingers touch the keyboard.
You fire up Claude Code.
Type with the confidence of someone who’s done this a thousand times: “Build me an AI chat interface using AI Elements.”
Claude starts coding.
It looks… plausible.
Convincing, even.
Then you spot it: import { AIChat } from '@ai-sdk/elements'
That import doesn’t exist. The component is called Conversation. Claude is hallucinating an API that sounds right but isn’t.
It’s writing fiction dressed up as code.
You correct it.
Claude apologizes—sweet, polite, completely unhelpful.
Tries again.
Different hallucination.
Round and round you go.
Like trying to teach someone to cook while they’re blindfolded and you’re speaking different languages.
The documentation is literally right there on your screen. But Claude can’t see it.
Well.
That used to be true.
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Here’s the Thing About AI and Documentation
Every week—every blessed week—new libraries launch.
The ones you already use? They’re dropping breaking changes like confetti at a wedding nobody wanted to attend.
Meanwhile, your AI coding agent is stuck in the past.
Claude Opus 4.1 doesn’t know about the library that launched last month. It definitely doesn’t know about the v2.0 that dropped while you were eating lunch yesterday.
(Is it weird that we expect AI to be omniscient? Like it should somehow absorb knowledge through the ethernet? Stay with me.)
You’ve probably tried the usual suspects:
The copy-paste marathon—where you dump documentation into the prompt until your context window explodes like an overfilled water balloon.
The MCP server hunt—searching for something that usually doesn’t exist. (Spoiler: it doesn’t.)
The Context7 lottery—sometimes brilliant, sometimes returns docs from the Mesozoic era.
The manual correction dance—where you become a human API reference for three hours. (Fun!)
Each approach fails spectacularly in its own special way.
Copy-pasting burns through 80% of your context before you write a single line of actual code. Good luck debugging when you’ve already consumed 100k tokens on documentation alone.
MCP servers are amazing. When they exist. Which is approximately never for the library you need right now.
Context7 is like a box of chocolates—you never know if you’re getting current docs or something from 2022. You’ll find out the hard way.
Manual correction? Sure, if your idea of a good time is playing “human API dictionary” until your eyes bleed.
There had to be a better way.
(There is.)
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Enter Claude Skills: Your Documentation Superpower
Imagine this: You could teach Claude ANY library’s documentation.
Permanently.
Not the copy-paste-and-pray method. Not the please-let-there-be-an-MCP-server wishful thinking.
Actual knowledge.
The kind Claude can reference intelligently, pulling only the relevant bits for each task.
Like having a senior developer who’s memorized every documentation page but only shares what you need to know right now.
Here’s what becomes possible:
Claude Skills package documentation in a way that makes Claude understand not just WHAT the API is, but HOW to use it correctly. The difference between knowing the words to a song and understanding why it makes people cry.
Once you create a skill, it works forever.
Every project.
Every session.
Perfect implementation every time.
(Is it magic? Kind of. But the boring, repeatable kind.)
Let me show you exactly how I turned brand-new AI Elements documentation into a Claude Skill. Then used it to build a complete AI chat application.
Without a single hallucination.
Ferpetesake, it actually worked.
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Step 1: Gather Your Documentation (2 Minutes, If You’re Slow)
Downloaded everything—component references, examples, tutorials, the works.
Dropped them in my project like this:
Here’s the thing: Grab everything. Even that weird edge-case page you think you’ll never need. That’s the page that’ll save your bacon at 3 AM when nothing else makes sense.
(Trust me on this one.)
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Step 2: Brainstorm Like You Mean It (5 Minutes)
Most people would jump straight into creating the skill here.
Don’t.
(Seriously. Stop. Put down the keyboard.)
First, you need to define exactly how you want Claude to use this documentation. Think of it like training a brilliant but literal-minded assistant—you need to be specific about expectations.
Here’s my exact prompt:
Prompt:
I want to create a skill that reads the docs in this folder @docs/ai-sdk-ai-elements-doc/.
The idea: whenever we work with AI elements or build an AI native app, we'll refer to the relevant docs first before building the app.
The docs are in markdown format and contain detailed information about the AI elements SDK including usage examples, and best practices.
Ask me clarifying questions until you are 95% confident you can complete this task successfully.
a. If the question is about choosing different options, please provide me with a list of options to choose from. Mark the option with a clear label, like a, b, c, etc.
b. If the question need custom input that is not in the list of options, please ask me to provide the custom input.
Always mark each question with a number, like 1/, 2/, 3/, etc. so that I can easily refer to the question number when I answer.
For each question, add your recommendation (with reason why) below the options. This would help me in making a better decision.
Watch what happens next.
Claude doesn’t just accept the task like an overeager intern. It asks targeted questions:
How should the skill activate?
Automatic (when AI Elements terms pop up)
Manual only (when you explicitly call it)
Hybrid (best of both worlds)
Where should documentation live?
Local markdown files
WebFetch from the mothership
Both (local with web backup)
I answer with quick picks. No dissertations needed.
Claude then creates a complete requirements document.
We’re talking 654 lines of specifications. It includes:
Activation triggers (automatic when components are mentioned—like a helpful friend who knows when to chime in)
4 intelligent routing modes
Smart multi-page fetching rules
Response format templates
Query interpretation patterns
This isn’t busy work.
This is Claude learning HOW you want it to think about this documentation.
Time invested: 5 minutes of Q&A.
(Worth every second.)
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Step 3: Transform Requirements Into Reality (3 Minutes)
Now for the satisfying part.
I tell Claude: “Let’s use the ‘skill-creator’ skill to create the skill”
(Yes, we’re using a skill to create a skill. It’s skills all the way down. Stay with me.)
Watch as Claude:
Packages all 39 markdown files (31 components plus the kitchen sink)
Creates intelligent routing rules
Builds activation triggers
Generates a searchable index
The result?
Your documentation is now a reusable Claude Skill.
Forever.
(Take a moment. This is big.)
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Step 4: Watch the Magic Happen (10 Minutes of Pure Joy)
Time to see if this actually works.
I tell Claude: “Read the @.notes/requirements.md, and use the ‘ai-elements’ skill to build the AI Chat Application.”
Claude recognizes the skill immediately:
Now here’s where it gets interesting.
Instead of guessing the API—or worse, making stuff up—Claude reads the actual docs:
INDEX.md for component reference
examples/chatbot.md for patterns
components/conversation.md for core components
components/prompt-input.md for input handling
Notice something?
Claude read 8 files out of 39. Not the entire documentation set. Just what it needed.
Surgical precision.
(This is the opposite of the copy-paste-everything approach. And it’s beautiful.)
Now Claude builds with the confidence of someone who actually knows what they’re doing:
Every import correct. Every API call accurate. Zero hallucinations.
Want proof this actually works? Here’s what I built:
The entire AI chat application builds perfectly:
Database schema with Prisma
API routes for chat sessions
Real-time streaming with AI Elements
Proper component composition
Error handling
State management
No back-and-forth. No corrections. No “actually, that’s not how it works.”
It. Just. Works.
(I may have done a small victory dance. Don’t judge.)
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Why This Isn’t Just Another MCP Alternative
“But wait,” you’re thinking. “Isn’t this what MCP servers do?”
Kind of. But also not at all.
MCP servers:
Require the library author to build one (good luck with that)
Need constant maintenance (who has time?)
Often lag behind latest versions (naturally)
You have zero control (hope you like their choices)
Claude Skills:
You create them yourself (15 minutes, tops)
Work with ANY documentation (even that obscure library from 2019)
Update when YOU want (not when someone else gets around to it)
Full control over what’s included (your docs, your rules)
But here’s the feature that makes me want to write poetry:
Claude Skills read intelligently.
When working with AI Elements, Claude didn’t inhale all 39 documentation files like some kind of context-window glutton. It read the 8 relevant ones. No waste. No bloat. Just what it needed.
Try that with copy-paste.
(Spoiler: you can’t.)
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The Compound Effect (Or: Why This Changes Everything)
Think about your current stack for a hot second:
React components library
Your database ORM
Payment provider SDK
Authentication library
UI component system
Analytics platform
Email service
File storage API
That weird library Bob insisted on using
Each one could be a Claude Skill.
Do the math with me:
1 library skill = 2 hours saved per project 10 library skills = 20 hours saved Your entire stack as skills = Never manually correct AI again
But wait. (There’s more.)
Version updates? Update the skill once. Every project gets the new version. Like magic, but boring and reliable.
Team knowledge? Share the skill. Everyone codes like they wrote the docs. Instant expertise, just add water.
New libraries? 15 minutes to perfect implementation. Even if it launched during your lunch break.
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Your Library Skills Arsenal: A Field Guide
The Golden Rules
Rule 1: Include Everything, Let Claude Filter
Don’t try to curate “only the important docs.” You’re not the documentation police.
Claude Skills are intelligent. They’ll find what’s relevant. Your job is comprehensive coverage. Be the completionist.
Rule 2: Update Regularly (Set a Calendar Reminder)
Monthly skill updates. Put it in your calendar. Title it “Feed the Skills.” Your future self will send you thank-you notes.
Rule 3: Create Composite Skills
Building with Next.js + Prisma + tRPC? Create a “nextjs-stack” skill with all three. One activation, complete stack knowledge.
(Why make three trips when one will do?)
Rule 4: Test in Isolation
Before using a library skill in production:
Create a simple test project
Ask Claude to build a basic example
Verify the generated code matches current docs
Trust, but verify.
Rule 5: Share Your Skills
That React Native Navigation skill you perfected? Your team needs it. That Stripe integration skill? The community wants it.
Build once. Help everyone.
(Be the hero.)
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Your Action Plan (Do This Today)
Step 1: Identify Your Most Frustrating Library
Which one causes the most AI hallucinations?
That new API you’re wrestling?
The library with the major update?
The complex SDK with 100+ endpoints?
Pick your nemesis.
Step 2: Gather Documentation (2 minutes)
Download or clone the docs. Create a folder. Done.
(Easier than making coffee.)
Step 3: Brainstorm Requirements (5 minutes)
Use my prompt. Answer the questions. Let Claude build comprehensive requirements.
No shortcuts here. Do the work.
Step 4: Create The Skill (3 minutes)
Run skill-creator. Package the documentation.
Watch as months of frustration evaporate.
Step 5: Test Immediately
Build something simple. Verify accuracy. Refine if needed.
(But honestly? It usually works perfectly the first time.)
Step 6: Use It Everywhere
Every project. Every feature. Perfect implementation.
No exceptions.
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The Future You’re Building (Whether You Know It Or Not)
Picture this: You open Claude Code six months from now.
Your skills library includes:
Every major framework (even the ones that don’t exist yet)
Your company’s internal SDKs (the undocumented ones)
That obscure library only you use (we all have one)
The cutting-edge tool that launched this morning
You type: “Build me a real-time collaborative editor with our standard stack”
Claude activates:
nextjs-15-skill
collaboration-sdk-skill
your-ui-components-skill
websocket-patterns-skill
Perfect implementation. First try. Every single time.
No more “Claude doesn’t know this library.”
No more debugging hallucinated APIs.
No more being a human API reference.
Just your documentation, permanently accessible, intelligently used.
(Is this what peace feels like?)
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Here’s What I Know to Be True
Every library you use regularly should be a Claude Skill.
Not because it’s trendy. Not because it’s the cool new thing. Not even because I said so.
Because spending 15 minutes creating a skill saves you hours of correction. Forever.
Because your team deserves consistent implementation without the learning curve.
Because you have better things to do than correct AI hallucinations all day.
(Like, literally anything else.)
Claude Skills aren’t just about saving time. They’re about eliminating an entire category of AI coding friction. The kind that makes you want to throw your laptop out the window.
So here’s my challenge:
Take that new library. The one with no MCP server. The one Claude keeps getting wrong. The one that’s been making you question your career choices.
Spend 15 minutes. Create the skill. Watch it work perfectly.
It took months. Every edge case handled. Every security hole plugged. Production-tested across three different apps.
And now you’re starting project number four.
Time to rebuild it. Again. From scratch.
Because that’s how AI works, right? It gives you a solution, not your solution.
Wrong.
Last week, I showed you how Claude Skills changed everything – letting you replicate YOUR exact patterns across every project.
Today, I’m going to show you exactly how to create your own Claude Skills.
By the end of this article, you’ll know how to turn any feature into a reusable skill that Claude Code can deploy perfectly every time.
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The Secret: It’s Not About Code, It’s About Documentation
Here’s what most developers get wrong about Claude Skills.
They think it’s about copying code files. Dumping your lib/auth folder into a skill and calling it done.
That’s not how it works.
Claude Skills aren’t code repositories.
They’re implementation guides that teach Claude your specific patterns, your architecture decisions, your way of solving problems.
And the key to creating a powerful skill?
Comprehensive documentation that captures not just WHAT your code does, but HOW and WHY it works.
Let me show you exactly how I turned my authentication system into the Claude Skill I demonstrated in Part 1.
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Step 1: Let GPT-5 Document Your Implementation (10 Minutes)
This is counterintuitive, but stay with me.
I don’t use Claude to document my Claude Skills. I use GPT-5.
Why? Because GPT-5 is meticulous. It’s the senior architect who notices every pattern, every decision, every subtle implementation detail.
Here’s my exact process:
I give GPT-5 this prompt:
I want to update the authentication implementation docs at
#file:authentication.md to match the current implementation of authentication for
this app.
Read the codebase, analyze how this app implemented the authentication, then
update the docs.
Ask me clarifying questions until you are 95% confident you can complete this task
successfully.
a. If the question is about choosing different options, please provide me with a list
of options to choose from. Mark the option with a clear label, like a, b, c, etc.
b. If the question need custom input that is not in the list of options, please ask me
to provide the custom input.
Always mark each question with a number, like 1/, 2/, 3/, etc. so that I can easily
refer to the question number when I answer.
For each question, add your recommendation (with reason why) below each
options. This would help me in making a better decision.
Notice the key elements:
95% confidence threshold (forces thoroughness)
Structured question format (speeds up the process)
Recommendations included (leverages GPT-5’s analysis)
Watch as GPT-5 systematically explores:
Authentication routes (/app/api/auth/**)
Library files (auth.ts, jwt.ts, rate-limit.ts)
Middleware implementation
Database schema
Environment variables
GPT-5 asks targeted questions:
I answer with just the option letters.
No lengthy explanations needed. GPT-5 already understands my intent.
The result?
A complete authentication implementation guide covering:
302 lines of detailed documentation. Every decision documented. Every pattern explained.
Time spent: 10 minutes.
Now, you might notice something different in my screenshots – I’m using GPT-5 in GitHub Copilot instead of my usual Codex.
The reason?
I’d hit my Codex weekly limits when writing this. (Yes, even I burn through those limits when I’m deep in development mode.)
But here’s what I discovered: GPT-5 in GitHub Copilot is an excellent substitute for Codex. In terms of performance – especially when it comes to analyzing codebases – I honestly can’t tell the difference.
Same meticulous analysis. Same comprehensive documentation. Same quality output.
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Step 2: Create ASCII Wireframes for the UX Flow (5 Minutes)
Here’s where most skill creators stop. They have the backend documentation.
But Claude Skills need to understand the FULL implementation – including the UI.
This is where ASCII Wireframes become your secret weapon.
I ask GPT-5:
Why ASCII instead of HTML mockups?
HTML mockup for login page: ~500 lines, ~15,000 tokens ASCII wireframe for login page: ~50 lines, ~1,500 tokens
Same information. 90% less tokens.
GPT-5 creates wireframes for every screen:
Every interaction mapped. Every flow documented. Claude will know EXACTLY what UI to build.
Total documentation time: 15 minutes.
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Step 3: Transform Documentation Into a Claude Skill (5 Minutes)
Now we have comprehensive documentation and wireframes. Time to turn them into a Claude Skill.
.claude/
skills/
skill-creator/ # The skill that creates skills
notes/
authentication.md # Our documentation
authentication_wireframes.md # Our wireframes
Start a new Claude Code session and ask:
Claude shows the available skills:
Now the magic moment:
Please use the skill-creator skill to create a new skill with the skill-creator that shows
how to set up authentication exactly like this app does. Please refer to the documentation
@.notes/authentication.md and wireframes @.notes/authentication_wireframes.md.
Watch as Claude:
Reads the skill-creator instructions
Explores your authentication codebase
Analyzes your documentation
Studies the wireframes
It’s not just copying files.
It’s understanding your implementation and transforming it into teachable instructions.
Using GPT-5 to document for Claude Skills isn’t random. It’s strategic.
GPT-5’s superpower: Meticulous analysis and comprehensive documentation Claude’s superpower: Following detailed instructions perfectly
When you combine them:
GPT-5 extracts every pattern and decision from your code
Claude Skills preserves that knowledge permanently
Claude Code implements it flawlessly every time
It’s like having a senior architect (GPT-5) document your best practices, then having infinite junior developers (Claude Code instances) who can implement those practices perfectly.
No knowledge loss. No pattern drift. No “I think I did it differently last time.”
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Common Mistakes to Avoid
Mistake #1: Skipping the Documentation Phase
“I’ll just copy my code files into the skill.”
Wrong.
Skills need context, not just code.
Without documentation, Claude won’t understand your architectural decisions.
Mistake #2: Forgetting the UI Wireframes
Backend-only skills create Frankenstein features.
Same logic, completely different UI.
Always include wireframes.
Mistake #3: Not Testing in a Clean Project
Always test your skill in a fresh project.
That’s where you’ll discover missing dependencies or assumptions.
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Your Skills Library Starts Today
Here’s your action plan:
1. Identify Your Most Reused Feature
What do you build in every project?
Authentication system?
Admin dashboard?
Payment integration?
File upload handling?
2. Document It With GPT-5 (15 minutes)
Use my exact prompt. Let GPT-5 extract every pattern.
Use skill-creator. Let Claude package your knowledge.
5. Test In a New Project
Deploy it. Use it. Refine it.
6. Repeat For Your Next Feature
Build your library one skill at a time.
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The Compound Effect Nobody Sees Coming
Every skill you create makes the next project easier.
But here’s what really happens:
Month 1: You create 3 skills (auth, payments, dashboard) Month 2: You create 5 more (file upload, search, notifications…) Month 3: You realize you can build entire apps in hours
By month 6?
You’re not coding anymore. You’re orchestrating.
“Use authentication-setup skill.”
“Use payment-processing skill.”
“Use admin-dashboard skill.”
Complete applications assembled from your battle-tested components.
Each implementation identical to your best work.
No quality degradation. No pattern drift. No forgotten edge cases.
This isn’t the future of development. It’s available right now.
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Part 3 Preview: Teaching Claude Any Library
Next week, I’ll show you something even more powerful.
How to create Claude Skills that teach Claude to perfectly integrate ANY library or SDK into your apps.
Imagine:
“Use the stripe-integration skill” → Your exact Stripe patterns
“Use the websocket-setup skill” → Your real-time architecture
“Use the testing-harness skill” → Your testing methodology
Not generic implementations. YOUR implementations.
But for now…
Open that project with your best authentication system.
Document it with GPT-5.
Turn it into a skill.
Watch as 10 minutes of work today saves you 10 hours next month.
What feature will you turn into a Claude Skill first?
Stop rebuilding.
Start packaging.
Now.
P.S. – Since creating my authentication-setup skill two weeks ago, I’ve deployed it to 6 different projects. Total time saved: 14 hours. Total consistency: 100%. Every deployment identical to my best implementation. That’s the power of turning your code into Claude Skills.
P.P.S. – The skill-creator skill itself is open source. You can find it at github.com/anthropics/skills. But the real magic? It’s in the skills YOU create from YOUR battle-tested code.