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Claude Md Generator

Organization
Varnan-Tech
claude-md-generator

Use when the user asks to generate or update a project's CLAUDE or AGENTS context file from a codebase scan. Writes a focused file under 100 lines containing only the non-obvious build commands, conventions, and gotchas Claude Code needs.

Overview

PublisherVarnan-Tech
Repositoryopendirectory
Skill nameclaude-md-generator
Stars
674
Forks
74
Bundled files
2
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 2 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by Varnan-Tech on GitHub. Read the source before you install it.

Installation

Install the Claude Md Generator AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/Varnan-Tech/opendirectory/tree/main/skills/claude-md-generator
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/Varnan-Tech/opendirectory.git /tmp/opendirectory
mkdir -p .claude/skills
cp -r /tmp/opendirectory/skills/claude-md-generator .claude/skills/claude-md-generator
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Claude Md Generator in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Claude Md Generator on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Claude Md Generator is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

CLAUDE.md Generator

Read the codebase. Write a CLAUDE.md that tells Claude exactly what it needs: no more, no less.


Critical rule: A good CLAUDE.md is under 100 lines. It contains only information Claude cannot derive from reading the code itself. Do not auto-write the file: always show the draft and wait for user approval first.

Code snippet rule: Never include inline code examples in CLAUDE.md. Instead use file.ts:42 references. Code in CLAUDE.md wastes tokens and goes stale.


Step 1: Detect Mode

Determine which of three modes to run:

create: No CLAUDE.md exists. Write one from scratch. update: A CLAUDE.md exists. Improve it without discarding custom content. audit: Score all CLAUDE.md files in the project A-F and output a quality report. If the user says "audit", "check", "review", or "grade" my CLAUDE.md, run audit mode.

bash
# Discover ALL CLAUDE.md locations
find . -name "CLAUDE.md" -not -path "*/node_modules/*" -not -path "*/.git/*" 2>/dev/null
ls ~/.claude/CLAUDE.md 2>/dev/null && echo "Global CLAUDE.md found"
ls .claude.local.md 2>/dev/null && echo ".claude.local.md found"

If multiple CLAUDE.md files are found: list them. Ask: "Found CLAUDE.md in [locations]. Should I update all of them or just [root]?"


Step 2: Audit Mode (skip to Step 3 if create/update)

For each CLAUDE.md found, score it A-F using this rubric:

CriterionWhat to check
CommandsBuild/test/lint commands present and runnable?
ArchitectureNon-obvious structure explained?
Non-obvious patternsGotchas, generated files, env var order documented?
ConcisenessUnder 100 lines? No obvious filler?
CurrencyCommands still match current package.json/Makefile?
ActionabilityCan a new contributor follow this without asking questions?

Score: 90-100 = A, 70-89 = B, 50-69 = C, 30-49 = D, 0-29 = F

Present as a table:

## CLAUDE.md Audit Report

| File | Score | Grade | Top Issues |
|------|-------|-------|-----------|
| ./CLAUDE.md | 72 | B | Missing gotchas section, test command outdated |
| ./packages/api/CLAUDE.md | 45 | D | No commands, 340 lines (too long), stale arch notes |

**Overall: B (72/100)**

Issues found:
- ./packages/api/CLAUDE.md: 340 lines: well over the 100-line target
- ./packages/api/CLAUDE.md: Test command references `jest` but package.json uses `vitest`
- ./CLAUDE.md: No Gotchas section: most valuable section is missing

After the report, ask: "Want me to fix any of these? (all / just root / specify)"

If user says yes, continue to Step 3 for each file they want fixed.


Step 3: Scan Project Structure

bash
# Project type and package manager
ls package.json yarn.lock pnpm-lock.yaml bun.lockb requirements.txt pyproject.toml Cargo.toml go.mod 2>/dev/null

# Top-level directory structure
find . -maxdepth 2 -type d \
  | grep -v node_modules | grep -v .git | grep -v __pycache__ \
  | grep -v ".next" | grep -v dist | grep -v build | sort

Step 4: Extract Build and Test Commands

bash
# npm/yarn/pnpm/bun scripts
cat package.json 2>/dev/null \
  | python3 -c "
import sys, json
d = json.load(sys.stdin)
for name, cmd in d.get('scripts', {}).items():
    print(f'{name}: {cmd}')
"

# Python, Go, Rust Makefiles
cat Makefile 2>/dev/null | grep -E "^[a-z].*:" | head -20

# Go
cat go.mod 2>/dev/null | head -5

# Rust
cat Cargo.toml 2>/dev/null | grep -E "^\[" | head -10

Identify the exact commands for: build, test (all), test (single file/name), dev server, lint/typecheck. Note any env vars required to run them.


Step 5: Find Code Style and Gotchas

bash
# Import aliases (most commonly missed)
python3 -c "
import json, sys
try:
    d = json.load(open('tsconfig.json'))
    paths = d.get('compilerOptions', {}).get('paths', {})
    if paths: print('Import aliases:', json.dumps(paths, indent=2))
except: pass
" 2>/dev/null

# Environment variables required
cat .env.example 2>/dev/null | grep -v "^#" | grep -v "^$" | head -20

# Auto-generated files (must not be edited)
find . -path "*/node_modules" -prune -o -name "*.ts" -print \
  | xargs grep -l "DO NOT EDIT\|@generated\|Generated by" 2>/dev/null | head -5

# Test setup requirements
cat jest.config.js jest.config.ts vitest.config.ts 2>/dev/null | head -30

# Database/migration setup
ls migrations/ prisma/ drizzle/ db/ 2>/dev/null

What counts as a Gotcha (include these, skip everything else):

  • Files that are auto-generated (must not edit)
  • Env vars required BEFORE tests run
  • Non-default import alias mappings
  • Test commands that require a running service
  • Known intentional quirks (workarounds, not bugs)

Step 6: Generate CLAUDE.md Draft with Gemini

Compile all findings and generate the draft:

bash
cat > /tmp/claude-md-request.json << 'ENDJSON'
{
  "system_instruction": {
    "parts": [{
      "text": "Write a CLAUDE.md file for a software project. Rules: (1) Under 100 lines total. (2) Only include what Claude cannot derive from reading the code. (3) No inline code examples: use file.ts:42 references instead. (4) Sections: Commands, Code Style (only non-defaults), Testing (only if setup needed), Gotchas (required: what trips people up). Skip any section that has nothing non-obvious to say. (5) All commands in code blocks. (6) Preferred order: short Project Overview (1-2 sentences, only if non-obvious), Commands, Architecture (only non-obvious structure), Code Style, Testing, Gotchas. (7) Do not use em dashes. (8) Output only the CLAUDE.md content, no commentary."
    }]
  },
  "contents": [{
    "parts": [{
      "text": "PROJECT_ANALYSIS_HERE"
    }]
  }],
  "generationConfig": {
    "temperature": 0.3,
    "maxOutputTokens": 2048
  }
}
ENDJSON

curl -s -X POST \
  "https://generativelanguage.googleapis.com/v1beta/models/gemini-2.0-flash:generateContent?key=$GEMINI_API_KEY" \
  -H "Content-Type: application/json" \
  -d @/tmp/claude-md-request.json \
  | python3 -c "import sys,json; d=json.load(sys.stdin); print(d['candidates'][0]['content']['parts'][0]['text'])"

Replace PROJECT_ANALYSIS_HERE with findings from Steps 3-5.

For large projects (50+ files): Add a @path pointer at the bottom of CLAUDE.md instead of inline detail:

markdown
## Extended Reference
See @docs/ai-context/architecture.md for full module map.
See @docs/ai-context/testing.md for integration test setup details.

Write the referenced files to docs/ai-context/ with the detail that would not fit in 100 lines.


Step 7: Self-QA

Before presenting the draft, check:

  • Under 100 lines (count: echo "$CONTENT" | wc -l)
  • No inline code examples (only file.ts:42 references or shell commands)
  • All commands in code blocks and runnable as-is
  • Gotchas section present with at least one real entry
  • No section that says only things obvious from the files
  • No em dashes
  • No marketing words or filler phrases ("This project uses React to...")
  • Import aliases documented if they exist
  • Auto-generated files marked "do not edit" if they exist

If any check fails, revise before presenting.


Step 8: Present Draft and Wait for Approval

Never write the file without user approval.

Present the draft in a code block:

## Draft CLAUDE.md ([N] lines)

[full draft content here]

---
Write this to CLAUDE.md? (yes / edit first / cancel)

If user says yes: write the file, then confirm: "CLAUDE.md written ([N] lines). Sections: [list of ## headers]."

If user says edit first: apply their edits, re-show the draft.

If user says cancel: stop.


What NOT to Include

  • Language/framework version ("This is a TypeScript project")
  • How the framework works (Claude already knows React, FastAPI, etc.)
  • List of all dependencies
  • Style rules the linter already enforces (indent size, quote style)
  • Content that duplicates README.md
  • Inline code examples or multi-line snippets
  • Anything that would be identical for any project using the same stack

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Claude Md Generator AI skill do?

Use when the user asks to generate or update a project's CLAUDE or AGENTS context file from a codebase scan. Writes a focused file under 100 lines containing only the non-obvious build commands, conventions, and gotchas Claude Code needs.

Why use Claude Md Generator on TypingMind?

Because you install it once and use it with any model. Claude Md Generator is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Claude Md Generator in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Varnan-Tech/opendirectory/tree/main/skills/claude-md-generator. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Claude Md Generator?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Claude Md Generator?

As many as you like. As long as a model supports skills, you can use Claude Md Generator with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Claude Md Generator AI skill free?

Yes. It is published on GitHub by Varnan-Tech under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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