llms-txt-checkerlisted

# LLMs.txt Checker Skill Audits any domain's AI-readiness by using `curl` to directly probe `robots.txt`, `llms.txt`, and `llms-full.txt`, then scores each file against a structured checklist and delivers a formatted report with pass/warn/fail findings and actionable fixes. The user provides **only a domain** (e.g. `anthropic.com` or `docs.example.com`). Claude uses `bash_tool` with `curl` commands to directly probe the domain — no guessing, no page-scraping required. --- ## How it works Instead of relying on web_fetch and hoping links surface organically, this skill uses **curl via bash_tool** to directly request the well-known paths for `robots.txt`, `llms.txt`, and `llms-full.txt`. This is reliable, fast, and works regardless of how the site is built. The curl commands follow HTTP redirects, capture response codes, and save content to temp files for auditing. --- ## Step-by-Step Workflow ### Step 1: Normalise the domain Take the user-provided input and strip any trailing slashes, `http://`, `https://`, or path segments to get a clean base domain (e.g. `docs.anthropic.com`). If the user provides a full URL like `https://docs.anthropic.com/en/home`, extract just `docs.anthropic.com`. --- ### Step 2: Fetch all three files via curl Run the following curl commands using `bash_tool`. Use `-L` to follow redirects, `-s` for silent mode, `-o` to save content, `-w` to capture HTTP status codes, and a reasonable timeout (`--max-time 10`). ```bash DOMAIN="<normalised-dom