Mk Llms

---
name: "mk-llms"
description: "Generate llms.txt files from project docs per the llmstxt.org spec, for AI-friendly documentation indexes and discoverability. Use to create or update llms.txt for AI assistants."
---

# llms.txt Generator

Generate [llms.txt](https://llmstxt.org/) files — LLM-friendly markdown indexes of project documentation.

> **Path convention:** Commands below assume cwd is `$(git rev-parse --show-toplevel)` (project root). Prefix paths with `"$(git rev-parse --show-toplevel)/"` when invoking from subdirectories.

## When to Use

- Project needs LLM-friendly documentation index
- User asks for "llms.txt", "LLM documentation", "AI-friendly docs"
- Publishing docs site and want AI discoverability
- After major documentation updates (Phase 6 Reflect)

Explicit: `the llms skill [path] [--full]`

## Workflow Integration

Operates in **Phase 6 (Reflect)** or on-demand. Output supports the `documenter` agent.

## Arguments

| Flag            | Effect                                            |
| --------------- | ------------------------------------------------- |
| (no args)       | Scan `./docs` directory                           |
| `path`          | Scan specific directory                           |
| `--full`        | Also generate `llms-full.txt` with inline content |
| `--output path` | Custom output location (default: project root)    |
| `--url base`    | Base URL prefix for links                         |

## Scripts

**Script-first approach** — the Python script handles all deterministic work (scanning, extracting, categorizing, generating). Codex only reviews and improves the output.

```bash
# Generate llms.txt (script does the heavy lifting)
.cursor/skills/.venv/bin/python3 .cursor/skills/llms/scripts/generate-llms-txt.py \
  --source ./docs [--output .] [--base-url https://example.com/docs] [--full]

# Preview metadata first (Codex reviews before generating)
.cursor/skills/.venv/bin/python3 .cursor/skills/llms/scripts/generate-llms-txt.py \
  --source ./docs --json
```

## Process

1. **Run script** — execute `generate-llms-txt.py --source <path> --json` to preview metadata
2. **Review metadata** — check project name, description, file categorization
3. **Generate** — run script again without `--json` to produce llms.txt
4. **Review output** — read generated llms.txt, improve descriptions if needed
5. **Validate** — check: H1 present, blockquote summary, valid link format, Optional section last
6. If `--full`: review llms-full.txt for completeness

## Output Format

```markdown
# {Project Name}

> {Brief project description with essential context.}

## {Section Name}

- [{Doc Title}]({url}): {Brief description}
- [{Another Doc}]({url}): {What this covers}

## Optional

- [{Less Important Doc}]({url}): {Supplementary info}
```

## References

| Reference                                             | When to load        | Content                              |
| ----------------------------------------------------- | ------------------- | ------------------------------------ |
| **[llms-txt-spec.md](./references/llms-txt-spec.md)** | Step 4 — generating | Full llmstxt.org specification rules |

## Failure Handling

| Failure                  | Recovery                                  |
| ------------------------ | ----------------------------------------- |
| No .md files found       | Report "No documentation found in {path}" |
| No H1 in doc file        | Use filename as title, warn user          |
| Output path not writable | Suggest alternative path                  |

## Constraints

- Never fabricate documentation content — only index what exists
- Follow llmstxt.org spec strictly
- Keep descriptions concise — one sentence per entry

## Gotchas

- **Python venv required**: run `npx mewkit setup` once from the project root before invoking this skill. Re-run after upgrading the toolkit.