mcpbeat Sign in

Quickgo Skill for Codex

Submit compact QuickGO requests for GO terms, annotations, and ontology traversal. Use when a user wants concise QuickGO summaries

3k tokens
context cost
the whole folder, loaded on every use
3
files
ships runnable scripts
0
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 quickgo-skill

What comes with it

10 836 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 QuickGO API calls.
  • Use base_url=https://www.ebi.ac.uk/QuickGO/services.
  • GO term lookups usually do not need max_items; annotation and traversal endpoints are better with limit=10 and max_items=10.
  • Send Accept: application/json in headers.
  • Re-run requests in long conversations instead of relying on older tool output.
  • Treat displayed ... in tool previews as UI truncation, not literal request content.

Execution behavior

  • Return concise markdown summaries from the script JSON by default.
  • Prefer these paths: ontology/go/terms/<id>, annotation/search, and ontology child or ancestor endpoints.
  • Treat annotation/search as upstream-fragile when QuickGO's annotation Solr backend is unavailable; fall back to ontology term lookup or UniProt GO annotations when appropriate.
  • If the user needs the full payload, set save_raw=true and report the saved file path.

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 QuickGO patterns:
  • {"base_url":"https://www.ebi.ac.uk/QuickGO/services","path":"ontology/go/terms/GO:0008150,GO:0003674","headers":{"Accept":"application/json"},"record_path":"results","max_items":10}
  • {"base_url":"https://www.ebi.ac.uk/QuickGO/services","path":"annotation/search","params":{"geneProductId":"P04637","limit":10},"headers":{"Accept":"application/json"},"record_path":"results","max_items":10}

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 and error.message.

Execution

echo '{"base_url":"https://www.ebi.ac.uk/QuickGO/services","path":"ontology/go/terms/GO:0006915","headers":{"Accept":"application/json"},"record_path":"results","max_items":10}' | 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
Protocolsio Integration
by christophacham
×4

Integration with protocols.io API for managing scientific protocols. This skill should be used when working with protocols.io to search, create, update, or publish protocols; manage protocol steps and materials; handle discussions and comments; organize workspaces; upload and manage files; or integrate protocols.io functionality into workflows. Applicable for protocol discovery, collaborative protocol development, experiment tracking, lab protocol management, and scientific documentation.

16k tokens
Tailored Resume Generator
by frostant
×4

Analyzes job descriptions and generates tailored resumes that highlight relevant experience, skills, and achievements to maximize interview chances

3k tokens
Excalidraw Diagram Generator
by github
vendor ×3

Generate Excalidraw diagrams from natural language descriptions. Use when asked to "create a diagram", "make a flowchart", "visualize a process", "draw a system architecture", "create a mind map", or "generate an Excalidraw file". Supports flowcharts, relationship diagrams, mind maps, and system architecture diagrams. Outputs .excalidraw JSON files that can be opened directly in Excalidraw.

36k tokens scripts
Executing Plans
by ZhanlinCui
×3

Use when you have a written implementation plan to execute in a separate session with review checkpoints

542 tokens
Anndata
by christophacham
×3

Data structure for annotated matrices in single-cell analysis. Use when working with .h5ad files or integrating with the scverse ecosystem. This is the data format skill—for analysis workflows use scanpy; for probabilistic models use scvi-tools; for population-scale queries use cellxgene-census.

16k tokens
Benchling Integration
by christophacham
×3

Benchling R&D platform integration. Access registry (DNA, proteins), inventory, ELN entries, workflows via API, build Benchling Apps, query Data Warehouse, for lab data management automation.

14k tokens
Biopython
by christophacham
×3

Comprehensive molecular biology toolkit. Use for sequence manipulation, file parsing (FASTA/GenBank/PDB), phylogenetics, and programmatic NCBI/PubMed access (Bio.Entrez). Best for batch processing, custom bioinformatics pipelines, BLAST automation. For quick lookups use gget; for multi-service integration use bioservices.

24k tokens
Cellxgene Census
by christophacham
×3

Query the CELLxGENE Census (61M+ cells) programmatically. Use when you need expression data across tissues, diseases, or cell types from the largest curated single-cell atlas. Best for population-scale queries, reference atlas comparisons. For analyzing your own data use scanpy or scvi-tools.

8k tokens

How to use it

Copy the folder

Take openai/quickgo-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.