Writing LLM Md

Writing LLM.md

Purpose

An LLM.md is a condensed, practical reference that gives AI assistants just enough context to use a library effectively without wading through full documentation. It prioritizes common patterns over exhaustive API coverage.

When to use this skill

• Creating documentation for a library or framework
• Writing context files for AI-assisted development
• Summarizing existing documentation for LLM consumption
• Any time you need to provide library context to AI assistants efficiently

File structure

Place LLM.md at the library root directory:

Core sections

1. TL;DR (Required)

Lead with what matters most. Include:

• One-sentence description of what the library does
• Primary use case
• Typical code snippet showing basic usage

Example:

## TL;DR
A promise-based HTTP client for browser and Node.js. Use when you need to make HTTP requests with automatic transforms and interceptors.

```javascript
import axios from 'axios';
const response = await axios.get('/api/users');

### 2. API at a glance
List the functions, but not every detail. Include:
- Function signatures with types
- Brief return value description
- One-line purpose
- Note on any gotchas

Example:
```markdown
## API at a Glance

| Function | Returns | Purpose |
|----------|---------|---------|
| `axios.get(url, config?)` | `Promise<Response>` | GET request with optional config |
| `axios.post(url, data?, config?)` | `Promise<Response>` | POST with automatic JSON serialization |
| `axios.create(config)` | `AxiosInstance` | Create instance with default config |
| `axios.interceptors` | `InterceptorManager` | Add request/response middleware |

Config options:
- `baseURL`: Prefix for all requests
- `headers`: Default headers
- `timeout`: Request timeout in ms (default: 0 = no timeout)
- `params`: Query parameters (auto-encoded)

3. Context LLMs Often Miss

Include implicit behaviors, defaults, and gotchas that trip up AI assistants:

## Implicit Behaviors

- Auto-JSON: Requests with object `data` are JSON-encoded automatically; responses with `Content-Type: application/json` are parsed automatically
- Default timeout: No timeout by default (`timeout: 0`)
- Error handling: Non-2xx responses throw; check `error.response.status`
- BaseURL merging: Relative URLs are resolved against `baseURL` using standard URL resolution rules
- Header casing: Headers are lowercased internally; don't rely on casing for logic

4. Anti-patterns

Show common mistakes and the correct approach:

## Anti-patterns

Don't manually stringify JSON:
```javascript
axios.post('/users', JSON.stringify(user), {
  headers: { 'Content-Type': 'application/json' }
});

Let axios handle serialization:

axios.post('/users', user); // Automatically stringified

## Writing principles

### Frontload examples
AI assistants pattern-match on code. Put working examples before explanations.

### Be opinionated
State the "right way" clearly. Don't present 5 equivalent options, pick the common recommended path.

### Use decision trees
```markdown
Choosing between sync and async:
- Use async/await for I/O bound operations (network, disk)
- Use sync methods only for in-memory operations with known-small data
- Never use sync methods in request handlers

Link, don't duplicate

Reference full documentation for edge cases:

For advanced interceptors, custom adapters, and request cancellation, see [Full Documentation](./docs/advanced.md).

Include real-world context

Mention when NOT to use the library:

## When NOT to use
- For simple static file serving, use `python -m http.server`
- For production reverse proxy, use nginx
- For WebSocket communication, use native WebSocket or Socket.io

Formatting guidelines

• Code blocks: Always specify language for syntax highlighting
• Tables: Use for API summaries and option references

Review checklist

Before finalizing an LLM.md:

• TL;DR section has working code example
• Common patterns cover 80% of real-world usage
• API at a glance lists possbiel functions
• Implicit behaviours and defaults are documented
• Any anti-patterns with corrections are shown
• Full documentation is linked for deep dives
• Examples are copy-pasteable and runnable

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