alphafold-skill
$
npx mdskill add openai/plugins/alphafold-skillFetch concise metadata and structure summaries from the AlphaFold Protein Structure Database API.
- Obtain structured data for protein predictions, UniProt details, and sequence annotations.
- Integrates with the AlphaFold EBI API via REST requests for biological data.
- Executes lookups based on provided identifiers, preferring reruns over stale context.
- Delivers results as concise markdown summaries by default, or raw JSON upon request.
SKILL.md
.github/skills/alphafold-skillView on GitHub ↗
---
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
---
## Operating rules
- Use `scripts/rest_request.py` for all AlphaFold API calls.
- Use `base_url=https://alphafold.ebi.ac.uk/api`.
- The script accepts `max_items`, but set it explicitly only when trimming array-heavy responses; single-entry lookups usually do not need it.
- For `sequence/summary` or `annotations`, start around `max_items=3` to `5`.
- Re-run the request if the conversation is long instead of trusting older tool output.
- Treat displayed `...` in tool previews as UI truncation, not part of the real request.
- If the user asks for full JSON, set `save_raw=true` and report the saved file path instead of pasting the payload into chat.
## Execution behavior
- Return concise markdown summaries from the script JSON by default.
- Return the script JSON verbatim only if the user explicitly asks for machine-readable output.
- Prefer these paths: `prediction/<qualifier>`, `uniprot/summary/<qualifier>.json`, `sequence/summary`, and `annotations/<qualifier>.json`.
- Keep sequence-style inputs compact and prefer rerunning instead of copying prior output back into context.
## Input
- Read one JSON object from stdin.
- Required fields: `base_url`, `path`
- Optional fields: `method`, `params`, `headers`, `json_body`, `form_body`, `record_path`, `response_format`, `max_items`, `max_depth`, `timeout_sec`, `save_raw`, `raw_output_path`
- Common AlphaFold patterns:
- `{"base_url":"https://alphafold.ebi.ac.uk/api","path":"prediction/Q5VSL9"}`
- `{"base_url":"https://alphafold.ebi.ac.uk/api","path":"uniprot/summary/Q5VSL9.json"}`
- `{"base_url":"https://alphafold.ebi.ac.uk/api","path":"annotations/Q5VSL9.json","params":{"type":"MUTAGEN"},"max_items":3}`
## Output
- Success returns `ok`, `source`, `path`, `method`, `status_code`, `warnings`, and either compact `records` or a compact `summary`.
- Use `raw_output_path` when `save_raw=true`.
- Failure returns `ok=false` with `error.code` such as `invalid_json`, `invalid_input`, `network_error`, or `invalid_response`.
## Execution
```bash
echo '{"base_url":"https://alphafold.ebi.ac.uk/api","path":"prediction/Q5VSL9"}' | python scripts/rest_request.py
```
## References
- No additional runtime references are required; keep the import package limited to this file and `scripts/rest_request.py`.
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