claude-md-generator: Design & UI for AI Agents | OpenAgentSkill

Overview

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.

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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.

# 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]?"

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

Criterion	What to check
Commands	Build/test/lint commands present and runnable?
Architecture	Non-obvious structure explained?
Non-obvious patterns	Gotchas, generated files, env var order documented?
Conciseness	Under 100 lines? No obvious filler?
Currency	Commands still match current package.json/Makefile?
Actionability	Can 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| ./CLAUDE.md | 72 | B | Missing gotchas section, test command outdated |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

# 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

# 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

# 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:

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:

## 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

View source ↗

File metadata

name: claude-md-generator
description: 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.
compatibility: [claude-code, gemini-cli, github-copilot]
author: OpenDirectory
version: 1.0.0

View original text

---
name: claude-md-generator
description: 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.
compatibility: [claude-code, gemini-cli, github-copilot]
author: OpenDirectory
version: 1.0.0
---

# 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:

| Criterion | What to check |
|-----------|--------------|
| Commands | Build/test/lint commands present and runnable? |
| Architecture | Non-obvious structure explained? |
| Non-obvious patterns | Gotchas, generated files, env var order documented? |
| Conciseness | Under 100 lines? No obvious filler? |
| Currency | Commands still match current package.json/Makefile? |
| Actionability | Can 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

Review the source

Skill source recorded

Skill instructions are recorded. This is not a runtime test, safety guarantee or compatibility certification.

Review before install: Avoid automatic install

License: MIT

Dependency or permission surface needs review
Permission surface may require sandboxing
Inconsistency in line count target: SKILL.md says 'under 100 lines' but evals expect 'under 200 lines'.
Evals mention 'Calls Gemini with analysis' which is not referenced in SKILL.md; may be a leftover from a different version.
Uses `python3` which may not be available on all systems; could fallback to other JSON parsers.
Quality score needs review
Permission surface needs review: secrets or environment access, shell or command execution
Dependency/runtime risk: command execution surface, credential or environment access
Permission surface: secrets or environment access, shell or command execution

Open full audit

Listed tools are metadata hints, not tested compatibility. Agent prompts are suggested handoffs.

Start with one small task

1Read the source. Confirm the input, expected output, dependencies and permissions.
2

Source & usage notes

Indexed

Repository metadata and review signals are advisory. Popularity, source discovery and successful execution are different facts.

Source repository: Varnan-Tech/opendirectory
License: MIT
Version: 1.0.0
Last GitHub push: Aug 16, 2026
Registry updated: Sep 5, 2026
Instruction path: skills/claude-md-generator/SKILL.md @ 62e437ab1340

Version reported in registry metadata; check source releases before relying on it.

Quality

72/100

Strong

Trust

56/100

Agent access

This page exposes the same decision, trust, audit, use-case, and install signals through the Registry API, so agents can rank this skill without scraping the UI.

Open install API LLM text format Open manifest Auto-resolve Plan

More details

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      "stars": "635 GitHub stars",
      "repoActivity": "635 stars, 68 forks",
      "lastPushed": "1mo since push",
      "license": "MIT",
      "repository": "https://github.com/Varnan-Tech/opendirectory/tree/main/skills/claude-md-generator",
      "install": "npx skills add Varnan-Tech/opendirectory --skill claude-md-generator",
      "installSafety": "standard package or runtime install path",
      "permissionSurface": "secrets or environment access, shell or command execution",
      "documentation": "Strong README/SKILL.md context",
      "agentOutcomes": "No agent outcome data yet"
    },
    "outcome_evidence": {
      "total": 0,
      "successes": 0,
      "failures": 0,
      "not_relevant": 0,
      "success_rate": null,
      "recent_success_rate": null,
      "recent_failure_rate": null,
      "install_attempts": 0,
      "install_success_rate": null,
      "risk_blocked": 0,
      "setup_required": 0,
      "avg_output_quality": null,
      "production_outcomes": 0,
      "last_outcome_at": null,
      "label": "No agent outcome data yet"
    },
    "auto_install": {
      "allowed": false,
      "sandbox_required": true,
      "reason": "Do not auto-install. Inspect the source, dependencies, and permission surface first."
    },
    "best_for": [
      "design-creative",
      "agent-skill"
    ],
    "known_risks": [
      "Inconsistency in line count target: SKILL.md says 'under 100 lines' but evals expect 'under 200 lines'.",
      "Quality score needs review",
      "Permission surface needs review: secrets or environment access, shell or command execution",
      "Dependency/runtime risk: command execution surface, credential or environment access",
      "Permission surface: secrets or environment access, shell or command execution"
    ]
  },
  "agent_proven": {
    "version": "agent-proven-v1",
    "score": 0,
    "tier": "unproven",
    "label": "Needs first agent run",
    "summary": "No agent outcome reports yet. Use Resolve, run one narrow sandbox task, then report the result.",
    "metrics": {
      "totalOutcomes": 0,
      "successfulOutcomes": 0,
      "failedOutcomes": 0,
      "installAttempts": 0,
      "installSuccessRate": null,
      "successRate": null,
      "recentSuccessRate": null,
      "recentFailureRate": null,
      "riskBlocked": 0,
      "setupRequired": 0,
      "notRelevant": 0,
      "avgOutputQuality": null,
      "avgTimeToUsefulMs": null,
      "productionOutcomes": 0,
      "humanReviewRequired": 0,
      "uniqueAgents": 0,
      "lastOutcomeAt": null
    },
    "signals": [],
    "penalties": [
      "No real agent outcome evidence yet"
    ]
  },
  "audit": {
    "score": 74,
    "risk_level": "needs_review",
    "risk_label": "Needs review",
    "warnings": [
      "Dependency or permission surface needs review",
      "Permission surface may require sandboxing",
      "Inconsistency in line count target: SKILL.md says 'under 100 lines' but evals expect 'under 200 lines'.",
      "Evals mention 'Calls Gemini with analysis' which is not referenced in SKILL.md; may be a leftover from a different version.",
      "Uses `python3` which may not be available on all systems; could fallback to other JSON parsers.",
      "Quality score needs review",
      "Permission surface needs review: secrets or environment access, shell or command execution",
      "Dependency/runtime risk: command execution surface, credential or environment access"
    ]
  },
  "safety_gate": {
    "tier": "blocked",
    "label": "Blocked for auto-install",
    "auto_install_policy": "block",
    "auto_install_allowed": false,
    "human_review_required": true,
    "blocked": true,
    "recommended_action": "Do not auto-install. Inspect the source, dependencies, and permission surface first."
  },
  "quality": {
    "score": 72,
    "label": "Strong"
  },
  "supply": {
    "track": "Design and creative production",
    "scenario": "Design and creative",
    "maintenance": "1mo since push",
    "risk": "Needs review"
  },
  "alternative_skills": [],
  "do_not_use_when": [
    "teams that need a vendor-supported SLA",
    "production agents without a repository review",
    "Inconsistency in line count target: SKILL.md says 'under 100 lines' but evals expect 'under 200 lines'.",
    "No OpenAgentSkill engagement data yet",
    "High-risk permission hints: Shell or command execution, Secrets or environment access",
    "Dependency or permission surface needs review",
    "Permission surface may require sandboxing",
    "Evals mention 'Calls Gemini with analysis' which is not referenced in SKILL.md; may be a leftover from a different version."
  ],
  "agent_contract": {
    "task_input": "Use claude-md-generator in an agent workflow",
    "recommended_action": "Do not auto-install. Inspect the source, dependencies, and permission surface first.",
    "install_policy": "block",
    "minimum_review_before_use": [
      "Trust: 64/100 Manual review",
      "Audit: 74/100 Needs review",
      "Safety: 30/100 Avoid automatic install",
      "Review repository, license, install command, and permission surface before production use."
    ],
    "expected_agent_output": {
      "selected_skill": "varnan-tech-claude-md-generator (claude-md-generator)",
      "install_command": "npx skills add Varnan-Tech/opendirectory --skill claude-md-generator",
      "risk_summary": "Needs review; Blocked for auto-install; Review before production",
      "verification_result": "Report the smallest successful task, files touched, warnings, and any missing setup."
    }
  },
  "outcome_feedback": {
    "endpoint": "https://www.openagentskill.com/api/agent/outcome",
    "method": "POST",
    "requires_resolve_event_id": true,
    "event_id_source": "Use install_receipt.outcome_feedback.event_id or feedback.event_id returned by /api/agent/resolve for the current task.",
    "expected_outcomes": [
      "success",
      "failed",
      "not_relevant",
      "blocked_by_risk",
      "setup_required"
    ],
    "payload_template": {
      "event_id": "<install_receipt.outcome_feedback.event_id or feedback.event_id from /api/agent/resolve>",
      "skill_slug": "varnan-tech-claude-md-generator",
      "task": "Use claude-md-generator in an agent workflow",
      "agent": "codex",
      "outcome": "success",
      "install_used": true,
      "risk_blocked": false,
      "setup_required": false,
      "task_success": true,
      "output_quality": 4,
      "error_type": null,
      "human_review_required": false,
      "workspace": "sandbox",
      "time_to_useful_ms": 120000,
      "notes": "Report the smallest successful task, setup friction, files touched, and risk notes."
    }
  },
  "endpoints": {
    "web": "https://www.openagentskill.com/skills/varnan-tech-claude-md-generator",
    "api": "https://www.openagentskill.com/api/agent/skills/varnan-tech-claude-md-generator",
    "audit": "https://www.openagentskill.com/skills/varnan-tech-claude-md-generator/audit",
    "eval": "https://www.openagentskill.com/api/agent/evals?slug=varnan-tech-claude-md-generator&task=Use%20claude-md-generator%20in%20an%20agent%20workflow&max_risk=medium",
    "resolve": "https://www.openagentskill.com/api/agent/resolve?task=Use%20claude-md-generator%20in%20an%20agent%20workflow&agent=codex&max_risk=medium",
    "receipt": "https://www.openagentskill.com/api/agent/receipt?task=Use%20claude-md-generator%20in%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text",
    "install": "https://www.openagentskill.com/api/skills/varnan-tech-claude-md-generator/install",
    "manifest": "https://www.openagentskill.com/api/registry/manifest/varnan-tech-claude-md-generator"
  }
}

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Creator: OpenDirectory
Source: Varnan-Tech/opendirectory
Indexed by: OpenAgentSkill community index

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