Alphafold Skill for Codex

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

3k tokens

context cost

the whole folder, loaded on every use

files

ships runnable scripts

copies elsewhere

how many repositories repackaged it

4915

stars on the repo

on the repository, not the skill itself

Install

one command, takes just this skill from the repository

npx skills add https://github.com/openai/plugins --skill alphafold-skill

What comes with it

10 826 bytes besides the instruction

agents/openai.yaml

scripts/rest_request.py

The instruction itself

6 sections, as written by the author

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

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.

Other skills for the same job

different authors, same section of the catalogue

Bioservices

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Moodle External API Development

by ComeOnOliver

×2

Create custom external web service APIs for Moodle LMS. Use when implementing web services for course management, user tracking, quiz operations, or custom plugin functionality. Covers parameter validation, database operations, error handling, service registration, and Moodle coding standards.

How to use it

Copy the folder

Take openai/alphafold-skill from the repository into ~/.claude/skills for personal use, or into .claude/skills inside a project.

Check the name does not clash

The agent identifies a skill by the name field in its header. Two skills with the same name cannot sit side by side — one of them will be ignored.