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llm-docs

by 5dlabs

Cognitive Task Orchestrator - GitOps on Bare Metal or Cloud for AI Agents

2🍴 1📅 Jan 25, 2026

SKILL.md


name: llm-docs description: Fetch LLM-optimized documentation from llms.txt endpoints for up-to-date API references agents: [blaze, rex, nova, tap, spark, grizz, bolt, cleo, cipher, tess, morgan, atlas, stitch] triggers: [llms.txt, documentation, official docs, framework docs, api reference]

LLM Documentation (llms.txt)

Many libraries provide LLM-optimized documentation at /llms.txt following the llms.txt standard.

Available Sources

When to Use llms.txt

Use llms.txt when:

  • Starting work with a library - Get the architectural overview first
  • Context7 lacks recent updates - llms.txt is always current
  • You need official API reference links - llms.txt links to authoritative docs
  • Understanding library structure - See what sections/features exist

llms.txt vs Context7

Aspectllms.txtContext7
SourceOfficial project filesIndexed documentation
GranularityFull overview + linksQuery-based chunks
FreshnessAlways currentDepends on indexing
Best forArchitecture overviewSpecific API questions

Recommended workflow: Start with llms.txt for overview, then use Context7 for specific implementation details.


Workflow

1. Fetch llms.txt for Overview

Use Firecrawl to fetch the llms.txt file:

firecrawl_scrape({ 
  url: "https://effect.website/llms.txt",
  formats: ["markdown"]
})

This returns a structured overview with:

  • Project description
  • Key documentation sections
  • Links to important resources

2. Fetch Full Documentation (if available)

For deeper context, some libraries provide llms-full.txt:

firecrawl_scrape({ 
  url: "https://effect.website/llms-full.txt",
  formats: ["markdown"]
})

Note: Full versions can be large. Only fetch when you need comprehensive documentation.

3. Follow Up with Context7

After understanding the structure from llms.txt, query specific topics:

context7_resolve_library_id({ libraryName: "effect typescript" })
→ /effect-ts/effect

context7_get_library_docs({ 
  libraryId: "/effect-ts/effect",
  topic: "schema validation with branded types"
})

Quick Reference

Frontend & UI

firecrawl_scrape({ url: "https://ui.shadcn.com/llms.txt" })     # shadcn/ui
firecrawl_scrape({ url: "https://tanstack.com/llms.txt" })      # TanStack (Router, Query, Table)

TypeScript Ecosystem

firecrawl_scrape({ url: "https://effect.website/llms.txt" })    # Effect TypeScript
firecrawl_scrape({ url: "https://zod.dev/llms.txt" })           # Zod schema validation
firecrawl_scrape({ url: "https://trpc.io/llms.txt" })           # tRPC typesafe APIs

Web Frameworks

firecrawl_scrape({ url: "https://elysiajs.com/llms.txt" })      # Elysia (Bun framework)
firecrawl_scrape({ url: "https://hono.dev/llms.txt" })          # Hono (Web Standards)
firecrawl_scrape({ url: "https://bun.sh/llms.txt" })            # Bun runtime

Database & ORM

firecrawl_scrape({ url: "https://orm.drizzle.team/llms.txt" })  # Drizzle ORM
firecrawl_scrape({ url: "https://www.prisma.io/llms.txt" })     # Prisma ORM
firecrawl_scrape({ url: "https://supabase.com/llms.txt" })      # Supabase

Authentication

firecrawl_scrape({ url: "https://www.better-auth.com/llms.txt" }) # Better Auth
firecrawl_scrape({ url: "https://clerk.com/llms.txt" })           # Clerk

Mobile & React Native

firecrawl_scrape({ url: "https://docs.expo.dev/llms.txt" })     # Expo
firecrawl_scrape({ url: "https://reactnative.dev/llms.txt" })   # React Native

Infrastructure & Deployment

firecrawl_scrape({ url: "https://vercel.com/llms.txt" })        # Vercel
firecrawl_scrape({ url: "https://turbo.build/llms.txt" })       # Turborepo

Payments

firecrawl_scrape({ url: "https://stripe.com/llms.txt" })        # Stripe

Testing

firecrawl_scrape({ url: "https://vitest.dev/llms.txt" })        # Vitest

Best Practices

  1. Check llms.txt first - Before diving into code, understand the library structure
  2. Use the registry - Reference llm-docs-registry.yaml for known URLs
  3. Prefer llms.txt over scraping random pages - It's curated for LLM consumption
  4. Combine sources - llms.txt → Context7 → specific doc pages
  5. Cache when appropriate - For repeated work, save llms.txt content locally

Score

Total Score

65/100

Based on repository quality metrics

SKILL.md

SKILL.mdファイルが含まれている

+20
LICENSE

ライセンスが設定されている

+10
説明文

100文字以上の説明がある

0/10
人気

GitHub Stars 100以上

0/15
最近の活動

1ヶ月以内に更新

+10
フォーク

10回以上フォークされている

0/5
Issue管理

オープンIssueが50未満

+5
言語

プログラミング言語が設定されている

+5
タグ

1つ以上のタグが設定されている

+5

Reviews

💬

Reviews coming soon