bgee-skill
par openai
Soumettre des requêtes SPARQL Bgee compactes pour les métadonnées d'expression de type sauvage sain et les motifs de recherche tenant compte de l'ontologie. Utiliser lorsque l'utilisateur souhaite des résumés Bgee concis ;…
npx skills add https://github.com/openai/plugins --skill bgee-skillOperating rules
- Use
scripts/sparql_request.pyfor all Bgee SPARQL work. - Start with small
SELECTorASKqueries and addLIMITearly. - Prefer ontology-aware, healthy wild-type expression questions over broad triple dumps.
- Use
query_pathfor longer SPARQL documents instead of pasting large inline queries. - Re-run requests in long conversations instead of relying on older tool output.
Execution behavior
- Return concise markdown summaries from the SPARQL JSON by default.
- Return raw results only if the user explicitly asks for machine-readable output.
- Default to JSON result format unless the user explicitly asks for text output.
Input
- Read one JSON object from stdin.
- Required field:
queryorquery_path - Optional fields:
method,params,response_format,max_items,max_depth,timeout_sec,save_raw,raw_output_path - Common Bgee patterns:
{"query":"ASK {}"}{"query":"SELECT * WHERE { ?s ?p ?o } LIMIT 3","max_items":3}
Output
- Success returns
ok,source, a compactsummary, andraw_output_pathwhensave_raw=true. - Failure returns
ok=falsewitherror.codesuch asinvalid_json,invalid_input,network_error, orinvalid_response.
Execution
echo '{"query":"ASK {}"}' | python scripts/sparql_request.py
References
- No additional runtime references are required; keep the import package limited to this file and
scripts/sparql_request.py.