SuperAPI AI Directory

mcp-research

Agents & models

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Updated 10-16 10:21

About this skill

Query: $ARGUMENTS

Goal: answer the query with minimum fetches. Targeted reads only — no broad crawling.

Sequence:

  1. PARSE — Extract from $ARGUMENTS:

    • Target source type: github | url | mcp-tool | search
    • Specific artifact: endpoint, schema, function, config key, page section
    • If source is ambiguous → ask before fetching
  2. LOCATE — One targeted lookup to find the exact resource:

    • GitHub repo: fetch https://api.github.com/repos/<owner>/<repo>/contents/<path> or raw file URL
    • API spec: fetch OpenAPI/AsyncAPI root, then only the relevant path object
    • DB schema: use available MCP tool (e.g. list-tables → describe only relevant tables)
    • Unknown source: one WebSearch with site: scoped query, pick top result
  1. FETCH — Read only what answers the query:

    • For large docs: fetch the section anchor/fragment if URL supports it
    • For OpenAPI specs: extract only the relevant paths + components/schemas entries
    • For GitHub files: prefer raw URL over HTML — less noise, fewer tokens
    • Stop after 2 fetches if answer is found
  2. SYNTHESIZE — Output:

SOURCE:  <url or tool:resource>
FINDING: <direct answer to the query — facts, not narrative>
SCHEMA:  <relevant fields/types if applicable>
NOTES:   <caveats, version constraints, gotchas>

Hard rules:

  • Never fetch a page just to find where the real page is — resolve first, then fetch
  • No recursive crawling — if a link looks relevant, include it in NOTES, don't follow it
  • Skip auth/login pages — note the access requirement and stop
  • If MCP tool is available for the source (DB, internal API), prefer it over web fetch
  • Max 3 fetches per query — if not resolved: report what was found + what's still missing