Generate Llms

Generate LLMs Files

Generate /llms.txt and /llms-full.txt files that help AI agents understand and use the agentconfig.org site content.

Overview

This skill generates machine-readable documentation files following the llmstxt.org standard:

• /llms.txt — A curated table of contents with links to detailed pages
• /llms-full.txt — Comprehensive markdown containing all site content
• /*.md — Page-specific markdown files (skills.md, agents.md, mcp.md, etc.)

Page Registry

Pages are automatically discovered from the page registry at site/src/data/pages.ts:

export const pages: readonly PageMeta[] = [
  {
    slug: 'skills',
    title: 'Skills Tutorial',
    description: 'How to create agent skills...',
    mdFile: 'skills.md',
    partNumber: 4,
  },
  // ... more pages
]

When creating a new page, add an entry to the registry to include it in the llms files.

When to Use

Use this skill when:

• You've updated content in the data files (site/src/data/*.ts)
• You've added a new page (remember to add it to the page registry!)
• Before deploying or releasing a new version of the site
• When an agent needs to understand what content should be in llms files

Data Sources

The llms files are generated from these TypeScript data files:

File Structure

site/public/
├── llms.txt           # Table of contents (llmstxt.org format)
├── llms-full.txt      # Complete site content in one file
├── skills.md          # Skills page content (rich markdown)
├── agents.md          # Agents page content (rich markdown)
├── hooks.md           # Hooks page content (rich markdown)
├── mcp.md             # MCP page content (rich markdown)
└── profiles.md        # Provider profiles content (rich markdown)

Generation Process

Step 1: Generate /llms.txt (Table of Contents)

The homepage llms.txt follows the strict llmstxt.org format:

• H1 with project name
• Blockquote with summary
• Optional paragraph (no headings)
• H2 sections with link lists only

# agentconfig.org

> A reference site for configuring AI coding assistants. Covers 13 AI primitives,
> provider comparison across GitHub Copilot, Claude Code, Cursor, and OpenAI Codex,
> and progressive tutorials for skills, instructions, hooks, and MCP.

## Pages

- [Homepage](https://agentconfig.org/): AI primitives reference, file tree, provider comparison
- [Skills Tutorial](https://agentconfig.org/skills): How to create agent skills following agentskills.io
- [Agent Instructions](https://agentconfig.org/agents): Project instructions across GitHub Copilot, Claude Code, Cursor, and OpenAI Codex

## Docs

- [Full site content](/llms-full.txt): Complete content for deep context
- [Skills page content](/skills.md): Skills tutorial with 5 example skills
- [Agents page content](/agents.md): Agents tutorial with code samples

## Optional

- [agentskills.io specification](https://agentskills.io/specification): The skills format
- [AGENTS.md specification](https://agents.md): Open format for coding agents

Step 2: Generate /llms-full.txt (Complete Content)

Run the generation script:

bun .github/skills/generate-llms/scripts/generate-llms-full.ts

This reads all data files and generates comprehensive markdown including:

1. Site overview with purpose and structure
2. All 13 AI primitives with full details:
   • Description
   • What it is
   • When to use it
   • What it prevents
   • What to combine it with
   • Provider implementations (GitHub Copilot, Claude Code, Cursor, and OpenAI Codex)
3. Provider comparison table showing support levels
4. Config file locations for all four providers
5. Skills tutorial with all concepts and 5 example skills
6. Agents tutorial with all sections and code samples

Step 3: Generate Page-Specific .md Files

/skills.md:

• Tutorial sections (Understanding the Spec, Progressive Disclosure, etc.)
• 5 example skills with full SKILL.md content
• Key takeaways for each example

/agents.md:

• 9 tutorial sections from beginner to advanced
• Code samples for AGENTS.md, CLAUDE.md, copilot-instructions.md
• Path-scoped rules, agent personas, monorepo strategies

Manual Generation

If the script isn't available, generate manually by:

1. Read each data file in site/src/data/
2. Extract the exported arrays/objects
3. Format as markdown following the templates below

Template: Primitive Entry

### {name}

{description}

**What it is:** {whatItIs}

**Use when:**
{useWhen as bullet list}

**Prevents:** {prevents}

**Combine with:** {combineWith as comma-separated list}

**Provider Implementations:**

| Provider | Implementation | Location | Support |
|----------|---------------|----------|---------|
| Copilot | {implementation} | {location} | {support} |
| Claude | {implementation} | {location} | {support} |

Template: Skill Example

### {displayName}

**Complexity:** {complexity}
**Demonstrates:** {demonstrates}

{description}

**Files:**

\`\`\`{language}
// {path}
{content}
\`\`\`

**Key Takeaways:**
{keyTakeaways as bullet list}

Validation

After generating, verify:

1. Links work — All internal links resolve
2. Content is current — Matches what's shown on the site
3. Format is correct — Valid markdown, proper headings
4. Size is reasonable — llms-full.txt should be comprehensive but not bloated

Example Prompts

Generate all llms files

Generate all the llms.txt files for agentconfig.org

Update after content change

I updated the primitives data, regenerate the llms files

Check what should be in llms-full.txt

What content should be included in llms-full.txt?