Generate and maintain llms.txt files for AI discoverability.

MITAuto-check passedMarketing & SEO

Install LLMs Txt

skills CLI
$ npx skills add thatrebeccarae/claude-marketing --skill llms-txt -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install thatrebeccarae/claude-marketing llms-txt --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/thatrebeccarae/claude-marketing.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/llms-txt .claude/skills/llms-txt && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
llms-txt
GitHub stars
161
Token cost
~1.6k tokens
SKILL.md length
795 words
Files
4
Skills in repo
55
Repo updated
First seen
Licence
MIT

At a glance

Generate and maintain llms.txt files for AI discoverability.

  • Works in 7 steps: Scan Repo Structure → Prioritize Content → Extract Metadata → …
  • Tasks that involve AI search optimization
  • SKILL.md covers Install, When to Use, What Is llms.txt and Usage, plus 4 more sections
  • Calls git

What it does

LLMs Txt is an agent skill from thatrebeccarae/claude-marketing. Generate and maintain llms.txt files for AI discoverability. Scans repos to create curated content maps that help AI answer engines surface your project accurately. Implements the llms.txt specification from Answer.AI.

Its SKILL.md is about 1.6k tokens, which your agent loads only when the skill is triggered. The skill folder holds 3 other files (for example `EXAMPLES.md` and `REFERENCE.md`).

It sits in Marketing & SEO, covering AI search optimization. The repository describes itself as: A full marketing department for Claude Code. Skill packs for Klaviyo, Shopify, GA4, Looker Studio, paid media, and more. Audit, optimize, and report using natural language. The licence is MIT.

When your agent uses it

  • Tasks that involve AI search optimization

Example prompts

  • “/llms-txt”

Workflow steps

7 steps, taken from the step headings in SKILL.md.

  1. Scan Repo Structure
  2. Prioritize Content
  3. Extract Metadata
  4. Generate llms.txt
  5. Optionally Generate llms-full.txt
  6. User Review
  7. Write to Repo Root

What it can do on your machine

Read from SKILL.md and the folder at commit a8a63ec. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • git

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Links to these hosts (documentation or services it may open):

    • llmstxt.org

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

LLMs Txt loads about 1.6k tokens when it runs. Until then it costs about 57 tokens; SKILL.md has 795 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~57
When it runs · the whole SKILL.md, loaded when a task matches
~1.6k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from thatrebeccarae/claude-marketing at commit a8a63ec, republished under its MIT licence (© thatrebeccarae). 795 words, ~1,629 tokens.

Download SKILL.mdSave it as .claude/skills/llms-txt/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.
name
llms-txt
description
Generate and maintain llms.txt files for AI discoverability. Scans repos to create curated content maps that help AI answer engines surface your project accurately. Implements the llms.txt specification from Answer.AI.
license
MIT
origin
custom
author
Rebecca Rae Barton
author_url
https://github.com/thatrebeccarae
metadata.version
1.0.0
metadata.category
seo
metadata.domain
ai-seo
metadata.updated
2026-03-19
metadata.tested
2026-03-19
metadata.tested_with
Claude Code v2.1

llms.txt Generator

Generate and maintain llms.txt files that help AI answer engines surface your project accurately.

Install

bash
git clone https://github.com/thatrebeccarae/claude-marketing.git && cp -r claude-marketing/skills/llms-txt ~/.claude/skills/

When to Use

  • Launching a new open-source project or documentation site
  • Major documentation restructure or content overhaul
  • Improving your project's visibility in AI search (ChatGPT, Perplexity, Google AI Overviews)
  • Onboarding a project to AI-friendly discoverability standards
  • Periodic refresh after significant repo changes

What Is llms.txt

llms.txt is a plain-text markdown file placed in a project's root that gives LLMs a curated map of the project's most important content. Think of it as robots.txt for AI comprehension — instead of telling crawlers where they can go, it tells them what matters and how the project is organized.

The specification was proposed by Answer.AI and is documented at llmstxt.org. Adoption is growing across developer tools, documentation sites, and open-source projects. Projects with an llms.txt are easier for AI to understand, cite, and recommend accurately.

Usage

/llms-txt generate [repo-path]

Scan a repository and generate a new llms.txt file. If no path is provided, uses the current working directory.

/llms-txt audit [repo-path]

Check an existing llms.txt for completeness, broken links, stale descriptions, and missing high-priority content. Produces a report with specific recommendations.

/llms-txt update [repo-path]

Refresh an existing llms.txt based on current repo state. Preserves manually curated descriptions while adding new content and removing references to deleted files.

Procedure

Step 1: Scan Repo Structure

Identify all documentation-relevant files in the repository:

  • README.md (root and significant subdirectories)
  • docs/ directory and its contents
  • API documentation (OpenAPI specs, API reference pages)
  • Tutorials, guides, and getting-started content
  • CHANGELOG.md, CONTRIBUTING.md, FAQ.md
  • Architecture and design decision docs
  • Configuration and deployment guides
  • Example directories with their own READMEs
Step 2: Prioritize Content

Rank discovered content by importance to an LLM trying to understand the project:

PriorityContent TypeWhy It Matters
P0README, Getting Started, API ReferenceEntry points — what the project is and how to use it
P1Tutorials, Guides, Architecture docsDeeper understanding — how it works and common workflows
P2CHANGELOG, CONTRIBUTING, FAQ, Config docsSupporting context — history, community, troubleshooting
Step 3: Extract Metadata

For each content page, extract or write:

  • Title: Clear, descriptive page title
  • URL or path: Where to find the content (full URL for hosted docs, relative path for repo files)
  • Description: One-line action-oriented summary of what the page covers
Step 4: Generate llms.txt

Assemble the file following the specification format:

  1. Title line: # Project Name
  2. Description block: 2-3 sentence summary of what the project does, who it is for, and its primary use case
  3. Sections: Group content logically (e.g., "Getting Started", "API", "Guides", "Community")
  4. Content items: Each item is a markdown link with a colon-separated description

See REFERENCE.md for the exact format specification.

Step 5: Optionally Generate llms-full.txt

For projects that benefit from it, generate an expanded version that inlines the actual content of key pages. This is useful for smaller projects where the full documentation fits in a single context window.

Show full SKILL.md (309 more words)Show less
Step 6: User Review

Present the generated llms.txt for review. Flag any decisions made during curation:

  • Content that was excluded and why
  • Descriptions that were inferred vs extracted from existing metadata
  • Sections where additional documentation would improve AI discoverability
Step 7: Write to Repo Root

Save llms.txt (and optionally llms-full.txt) to the repository root.

For projects with hosted documentation sites, also note the recommended placement for the hosted version (site root, e.g., https://docs.example.com/llms.txt).

Hosted Docs and GitHub Pages

If the project has a documentation site (GitHub Pages, ReadTheDocs, Docusaurus, etc.):

  • Generate llms.txt with full URLs pointing to the hosted docs, not repo file paths
  • Place the file where it will be served at https://yourdomain.com/llms.txt
  • For GitHub Pages: add llms.txt to the docs source directory so it deploys automatically
  • Consider adding llms.txt to your sitemap or linking it from robots.txt

Key Principles

  1. Curate, don't dump. An llms.txt that lists every file in the repo is worse than useless. Select the 10-30 most important pages that give an LLM the clearest picture of the project.
  2. Prioritize entry points. The first few items should answer: what is this, who is it for, and how do I start?
  3. Keep descriptions action-oriented. "How to configure authentication for SSO providers" beats "Authentication configuration page."
  4. Match the reader's mental model. Organize sections the way a newcomer would learn the project, not the way the repo is structured.
  5. Maintain freshness. Stale llms.txt with broken links or outdated descriptions erodes trust. Run /llms-txt audit after major documentation changes.

Integration with Other Skills

  • aeo-geo-optimizer — llms.txt complements broader AI search optimization; use both for maximum AI discoverability
  • technical-seo-audit — Ensure AI crawlers can access your docs before generating llms.txt
  • github-readme — A strong README is the foundation of a good llms.txt; optimize it first

For the full specification format, priority ranking criteria, and placement guidance, see REFERENCE.md.

© thatrebeccarae, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 3 other files in skills/llms-txt of thatrebeccarae/claude-marketing.

  • SKILL.md
  • EXAMPLES.md
  • LICENSE
  • REFERENCE.md

Open the folder on GitHubat commit a8a63ec

Compare with similar skills

LLMs Txt next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

LLMs Txt compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
LLMs Txt this skillthatrebeccarae/claude-marketing161—~1.6kAutomated safety check: PassMIT
Geo Fundamentalswasp-lang/wasp19k9 repos~861Automated safety check: PassMIT
SEO GeoReScienceLab/opc-skills1.8k4 repos~2.1kAutomated safety check: PassApache-2.0
GEO-First SEO Audit Toolzubair-trabzada/geo-seo-claude11k—~2.8kAutomated safety check: NotesMIT
GEO Monthly Delta Reportzubair-trabzada/geo-seo-claude11k—~2.4kAutomated safety check: NotesMIT
SEO DataforseoAgriciDaniel/codex-seo7992 repos~4.6kAutomated safety check: PassMIT

Similar skills

  • Geo Fundamentals

    wasp-lang/wasp

    Generative Engine Optimization for AI search engines (ChatGPT, Claude, Perplexity).

    19k GitHub starsUsed in 9 repos~861 tokens
    Marketing & SEOAuto-check passed
  • SEO Geo

    ReScienceLab/opc-skills

    SEO & GEO (Generative Engine Optimization) for websites. An agent skill from ReScienceLab/opc-skills.

    1.8k GitHub starsUsed in 4 repos~2.1k tokens
    Marketing & SEOAuto-check passed
  • GEO-First SEO Audit Tool

    zubair-trabzada/geo-seo-claude

    Audits a website for AI search visibility across ChatGPT, Claude, Perplexity and Google AI Overviews while checking traditional SEO, schema and E-E-A-T content quality.

    11k GitHub stars~2.8k tokensUpdated yesterday
    Marketing & SEOAuto-check: notes
  • GEO Monthly Delta Report

    zubair-trabzada/geo-seo-claude

    Compares a baseline and a current GEO audit for a client, calculates score changes and action item progress, and writes a monthly progress report.

    11k GitHub stars~2.4k tokensUpdated yesterday
    Marketing & SEOAuto-check: notes
  • SEO Dataforseo

    AgriciDaniel/codex-seo

    Live SEO data via DataForSEO MCP server. An agent skill from AgriciDaniel/codex-seo.

    799 GitHub starsUsed in 2 repos~4.6k tokens
    Marketing & SEOAuto-check passed
  • Fire Your SEO Agency

    leopard627/fire-your-seo-agency

    SEO·AEO·GEO·LLMO·NEO(네이버) 다섯 레인을 진단하고 직접 구현하며, 인용되는 콘텐츠를 계속 생산하는 서브 블로그·콘텐츠 운영 파이프라인까지 세팅하는 스킬.

    711 GitHub stars~1.1k tokensUpdated 15 days ago
    Marketing & SEOAuto-check passed

More from thatrebeccarae/claude-marketing

All 55 skills in this repo
  • Google Analytics

    thatrebeccarae/claude-marketing

    Analyze Google Analytics data, review website performance metrics, identify traffic patterns, and suggest data-driven improvements.

    161 GitHub starsUsed in 3 repos~1.3k tokens
    Auto-check: notes
  • Content Creator

    thatrebeccarae/claude-marketing

    Comprehensive content marketing toolkit with brand voice analysis, SEO optimization scripts, content frameworks, social media strategy, and content calendar planning.

    161 GitHub stars~1.1k tokensUpdated 4 mo ago
    Auto-check passed
  • Klaviyo Analyst

    thatrebeccarae/claude-marketing

    Klaviyo marketing operations and analyst expertise. An agent skill from thatrebeccarae/claude-marketing.

    161 GitHub stars~5k tokensUpdated 4 mo ago
    Auto-check: notes
  • Klaviyo Developer

    thatrebeccarae/claude-marketing

    Klaviyo API and developer integration expertise. An agent skill from thatrebeccarae/claude-marketing.

    161 GitHub stars~4.9k tokensUpdated 4 mo ago
    Auto-check: notes
  • Looker Studio

    thatrebeccarae/claude-marketing

    Looker Studio (formerly Google Data Studio) expertise. An agent skill from thatrebeccarae/claude-marketing.

    161 GitHub stars~3.6k tokensUpdated 4 mo ago
    Auto-check: notes
  • Shopify

    thatrebeccarae/claude-marketing

    Shopify e-commerce platform marketing expertise. An agent skill from thatrebeccarae/claude-marketing.

    161 GitHub stars~2.4k tokensUpdated 4 mo ago
    Auto-check: notes

Categories

Questions about LLMs Txt

What does LLMs Txt do?

Generate and maintain llms.txt files for AI discoverability. LLMs Txt is an agent skill from thatrebeccarae/claude-marketing.txt files for AI discoverability.

When should I use LLMs Txt?

LLMs Txt fits situations like: tasks that involve AI search optimization.

How do I install LLMs Txt in Claude Code?

Run `npx skills add thatrebeccarae/claude-marketing --skill llms-txt -a claude-code`. Or copy the skill folder (skills/llms-txt in thatrebeccarae/claude-marketing) into .claude/skills/llms-txt in your project. Claude Code loads it when a task matches its description.

How do I install LLMs Txt in Codex?

Run `npx skills add thatrebeccarae/claude-marketing --skill llms-txt -a codex`. Or copy the skill folder (skills/llms-txt in thatrebeccarae/claude-marketing) into .agents/skills/llms-txt in your project. Codex loads it when a task matches its description.

Can I use LLMs Txt in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add thatrebeccarae/claude-marketing --skill llms-txt -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/llms-txt, .gemini/skills/llms-txt, .github/skills/llms-txt and .opencode/skills/llms-txt in your project.

What does LLMs Txt need to run?

Going by SKILL.md and its folder, LLMs Txt needs the command-line tools its instructions call (git).

Does LLMs Txt access the network?

SKILL.md names 1 domain. As links in the text: llmstxt.org. This is read from the text; nothing was executed.

Is LLMs Txt safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does LLMs Txt use?

LLMs Txt is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does LLMs Txt use?

About 1.6k tokens (SKILL.md is roughly 6.5k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to LLMs Txt?

Skills that share tags, products or a category with LLMs Txt: Geo Fundamentals (wasp-lang/wasp, 19k stars), SEO Geo (ReScienceLab/opc-skills, 1.8k stars), GEO-First SEO Audit Tool (zubair-trabzada/geo-seo-claude, 11k stars) and GEO Monthly Delta Report (zubair-trabzada/geo-seo-claude, 11k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains LLMs Txt?

thatrebeccarae (a GitHub user) maintains it in thatrebeccarae/claude-marketing, which has 161 GitHub stars. The repository holds 55 skills in this directory. The repository was last updated on May 14, 2026.

Source: thatrebeccarae/claude-marketing on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.