Update to Life Science Research

{
  "name": "alphafold-skill",
  "description": "Submit compact AlphaFold Protein Structure Database API requests for prediction, UniProt summary, sequence summary, and annotation lookups. Use when a user wants AlphaFold metadata or concise structure summaries",
  "included_files": [
    {
      "relative_path": "agents/openai.yaml",
      "size_in_bytes": 98
    },
    {
      "relative_path": "scripts/rest_request.py",
      "size_in_bytes": 10728
    }
  ],
  "skill_md_contents": "---\nname: alphafold-skill\ndescription: Submit compact AlphaFold Protein Structure Database API requests for prediction, UniProt summary, sequence summary, and annotation lookups. Use when a user wants AlphaFold metadata or concise structure summaries\n---\n\n## Operating rules\n- Use `scripts/rest_request.py` for all AlphaFold API calls.\n- Use `base_url=https://alphafold.ebi.ac.uk/api`.\n- The script accepts `max_items`, but set it explicitly only when trimming array-heavy responses; single-entry lookups usually do not need it.\n- For `sequence/summary` or `annotations`, start around `max_items=3` to `5`.\n- Re-run the request if the conversation is long instead of trusting older tool output.\n- Treat displayed `...` in tool previews as UI truncation, not part of the real request.\n- If the user asks for full JSON, set `save_raw=true` and report the saved file path instead of pasting the payload into chat.\n\n## Execution behavior\n- Return concise markdown summaries from the script JSON by default.\n- Return the script JSON verbatim only if the user explicitly asks for machine-readable output.\n- Prefer these paths: `prediction/<qualifier>`, `uniprot/summary/<qualifier>.json`, `sequence/summary`, and `annotations/<qualifier>.json`.\n- Keep sequence-style inputs compact and prefer rerunning instead of copying prior output back into context.\n\n## Input\n- Read one JSON object from stdin.\n- Required fields: `base_url`, `path`\n- Optional fields: `method`, `params`, `headers`, `json_body`, `form_body`, `record_path`, `response_format`, `max_items`, `max_depth`, `timeout_sec`, `save_raw`, `raw_output_path`\n- Common AlphaFold patterns:\n  - `{\"base_url\":\"https://alphafold.ebi.ac.uk/api\",\"path\":\"prediction/Q5VSL9\"}`\n  - `{\"base_url\":\"https://alphafold.ebi.ac.uk/api\",\"path\":\"uniprot/summary/Q5VSL9.json\"}`\n  - `{\"base_url\":\"https://alphafold.ebi.ac.uk/api\",\"path\":\"annotations/Q5VSL9.json\",\"params\":{\"type\":\"MUTAGEN\"},\"max_items\":3}`\n\n## Output\n- Success returns `ok`, `source`, `path`, `method`, `status_code`, `warnings`, and either compact `records` or a compact `summary`.\n- Use `raw_output_path` when `save_raw=true`.\n- Failure returns `ok=false` with `error.code` such as `invalid_json`, `invalid_input`, `network_error`, or `invalid_response`.\n\n## Execution\n```bash\necho '{\"base_url\":\"https://alphafold.ebi.ac.uk/api\",\"path\":\"prediction/Q5VSL9\"}' | python scripts/rest_request.py\n```\n\n## References\n- No additional runtime references are required; keep the import package limited to this file and `scripts/rest_request.py`.\n"
}