Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/cgyudistira/agentkit/api-documentation-generatornpx skills add cgyudistira/agentkit --skill api-documentation-generatorgit clone --depth 1 https://github.com/cgyudistira/agentkitWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00025 | $0.02768 |
| Opus 5 | $0.00013 | $0.01384 |
| Sonnet 5 | $0.00005 | $0.00554 |
| Haiku 4.5 | $0.00003 | $0.00277 |
Grade B, and why
api-documentation-generator scanned grade B with 2 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Sends data to an external URLmediumData exfiltration
A POST to an outside endpoint may be telemetry or may be exfiltration; either way the mod talks to somewhere, and you should know where.
response = requests.post( 'https://api.example.com/api/v1/users', Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -X POST https://api.example.com/api/v1/users \ This is a copy
97% identical to api-documentation-generator — 2 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 485 lines — stays where its author put it; the contents beside it link to each section on GitHub.
API Documentation Generator
Overview
Automatically generate clear, comprehensive API documentation from your codebase. This skill helps you create professional documentation that includes endpoint descriptions, request/response examples, authentication details, error handling, and usage guidelines.
Perfect for REST APIs, GraphQL APIs, and WebSocket APIs.
When to Use This Skill
- Use when you need to document a new API
- Use when updating existing API documentation
- Use when your API lacks clear documentation
- Use when onboarding new developers to your API
- Use when preparing API documentation for external users
- Use when creating OpenAPI/Swagger specifications
How It Works
Step 1: Analyze the API Structure
First, I'll examine your API codebase to understand:
- Available endpoints and routes
- HTTP methods (GET, POST, PUT, DELETE, etc.)
- Request parameters and body structure
- Response formats and status codes
- Authentication and authorization requirements
- Error handling patterns
Step 2: Generate Endpoint Documentation
For each endpoint, I'll create documentation including:
Endpoint Details:
- HTTP method and URL path
- Brief description of what it does
- Authentication requirements
- Rate limiting information (if applicable)
Request Specification:
- Path parameters
- Query parameters
- Request headers
- Request body schema (with types and validation rules)
Response Specification:
- Success response (status code + body structure)
- Error responses (all possible error codes)
- Response headers
Code Examples:
- cURL command
- JavaScript/TypeScript (fetch/axios)
- Python (requests)
- Other languages as needed
Step 3: Add Usage Guidelines
I'll include:
- Getting started guide
- Authentication setup
- Common use cases
- Best practices
- Rate limiting details
- Pagination patterns
- Filtering and sorting options
Step 4: Document Error Handling
Clear error documentation including:
- All possible error codes
- Error message formats
- Troubleshooting guide
- Common error scenarios and solutions
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2d ago First seen · 485 lines · 25 tokens per session scan B 4b4c6a672810
api-documentation-generator is a skill published in the GitHub repository cgyudistira/agentkit (2 stars, last pushed 6mo ago), licensed MIT. It adds 25 tokens to every session and 2,768 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it B with 2 findings (sends data to an external url, makes network calls). It is 97% identical to api-documentation-generator, differing in 2 lines, and is treated as a copy.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
brainstorming
You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.
auto-perf-optimize
Run agent-driven VS Code performance or memory investigations. Use when asked to launch Code OSS, automate a VS Code scenario, run the Chat memory smoke runner, capture renderer heap snapshots, take workflow screenshots, compare run summaries, or drive a repeatable scenario before heap-snapshot analysis.
chat-perf
Run chat perf benchmarks and memory leak checks against the local dev build or any published VS Code version. Use when investigating chat rendering regressions, validating perf-sensitive changes to chat UI, or checking for memory leaks in the chat response pipeline.
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…