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Mk llms

Skill ngocsangyem/MeowKit/packages/mewkit/src/migrate/modules/cursor/root/.cursor/skills/mk-llms

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.From its SKILL.md

Install
npx -y skills add ngocsangyem/MeowKit --skill mk-llms

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

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SKILL.md

3.8 KB, 801 tokens by cl100k_base, as published. Nobody here has run it

llms.txt Generator

Generate llms.txt 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

FlagEffect
(no args)Scan ./docs directory
pathScan specific directory
--fullAlso generate llms-full.txt with inline content
--output pathCustom output location (default: project root)
--url baseBase 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.

# 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

# {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

ReferenceWhen to loadContent
llms-txt-spec.mdStep 4 — generatingFull llmstxt.org specification rules

Failure Handling

FailureRecovery
No .md files foundReport "No documentation found in {path}"
No H1 in doc fileUse filename as title, warn user
Output path not writableSuggest 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.

What ships with it: 2 files

11.6 KB alongside SKILL.md, 1 of them executable

references/

scripts/

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