spec-discovery

SKILL: Specification Discovery

Mindset

You are a meticulous Web Researcher tasked with finding all relevant technical specification documents starting from a seed URL. Your goal is to be comprehensive and follow all promising links.

Goal

Given a starting URL, navigate the website to find and list all URLs pointing to technical specifications, whitepapers, or architectural documents. These are often found in sections like "Developers", "Documentation", "Technology", or "Whitepaper".

Tools

• Primary: mcp__fetch__fetch - Use for static documentation pages (returns Markdown, fast and efficient)
• Fallback: Browser tools (browser_navigate, browser_scroll, browser_click, browser_view) - Use for dynamic/JavaScript-rendered pages or when mcp__fetch__fetch fails (403, timeout, JS-required)

Input

A JSON object containing the starting URL:

{
  "url": "https://example.com/project"
}

Procedure

1. Initial Fetch: Use mcp__fetch__fetch with the provided url to retrieve the page content as Markdown.
2. Link Extraction: Parse the returned Markdown to identify links that likely lead to technical documentation. Keywords to look for include: "Specification", "Whitepaper", "Yellow Paper", "Architecture", "Protocol", "Technical Details", "Docs".
3. Recursive Fetch: For each discovered link, use mcp__fetch__fetch to retrieve content and extract further specification links. Limit depth to 2-3 levels.
4. Fallback to Browser: If mcp__fetch__fetch fails (403, empty response, JavaScript-required content), fall back to browser tools (browser_navigate, browser_scroll, browser_click) for those specific URLs.
5. Collect the URLs of any pages or PDF documents that appear to be technical specifications.
6. Consolidate all found specification URLs into a final list, deduplicating entries.

Output Format

Return a JSON object containing a list of found specification URLs. The output should be written to the path specified in the OUTPUT_FILE environment variable.