Agent Skills
› openai/plugins
› opentargets-skill
opentargets-skill
GitHub用于提交Open Targets Platform的GraphQL查询，获取靶点、疾病、药物等数据摘要及关联疾病热力图。通过脚本处理输入并返回简洁Markdown或原始JSON结果。
触发场景
需要Open Targets平台的数据查询
生成关联疾病证据矩阵或气泡网格
安装
npx skills add openai/plugins --skill opentargets-skill -g -y
SKILL.md
Frontmatter
{
"name": "opentargets-skill",
"description": "Submit compact Open Targets Platform GraphQL requests for target, disease, drug, variant, study, and search data, including associated-disease datasource heatmap matrices. Use when a user wants concise Open Targets summaries or per-datasource evidence context"
}
Operating rules
- Use
scripts/opentargets_graphql.pyfor all Open Targets GraphQL work. - Use
scripts/opentargets_disease_heatmap.pywhen the user wants the associated-disease bubble grid or a disease-by-datasource evidence matrix. - The script accepts
max_items; for nested GraphQL results, start withmax_items=3to5. - Keep GraphQL selection sets narrow and page connection-style fields conservatively.
- Use
query_pathfor long GraphQL documents instead of pasting large inline query strings. - Re-run requests in long conversations instead of relying on earlier tool output.
- Treat displayed
...in tool previews as UI truncation, not part of the real query.
Execution behavior
- Return concise markdown summaries from the script JSON by default.
- Return the JSON verbatim only if the user explicitly asks for machine-readable output.
- Prefer targeted GraphQL queries that select only the fields needed for the user task.
- Use schema introspection only when necessary; do not dump large schema payloads into chat.
- For the associated-disease heatmap, treat
datasourceScoresas evidence-source breadth/context. Do not treat heatmap breadth alone as proof of causal target assignment, mechanism, or direction of effect.
Input
- Read one JSON object from stdin.
- Required field:
queryorquery_path - Optional fields:
variables,max_items,max_depth,timeout_sec,save_raw,raw_output_path - Common Open Targets patterns:
{"query":"query { __typename }"}{"query":"query searchAny($q: String!) { search(queryString: $q) { total hits { entity score object { ... on Target { id approvedSymbol } } } } }","variables":{"q":"MST1"},"max_items":3}
Output
- Success returns
ok,source,top_keys, a compactsummary, andraw_output_pathwhensave_raw=true. - Failure returns
ok=falsewitherror.codesuch asinvalid_json,invalid_input,network_error,invalid_response, orgraphql_error.
Execution
echo '{"query":"query { __typename }"}' | python scripts/opentargets_graphql.py
Associated-disease heatmap helper:
echo '{
"ensembl_id":"ENSG00000186868",
"page_size":50,
"max_pages":4,
"disease_name_filter":"alzh"
}' | python scripts/opentargets_disease_heatmap.py
The helper paginates associatedDiseases, collects datasourceScores, and returns:
matrix.columns: datasource IDs plus display labelsmatrix.rows: diseases withdatasource_scoressummary.rows_preview: top datasource signals per disease
Use the disease-name filter as a client-side substring filter similar to the UI. If you later need the overall association score column, inspect the GraphQL row type first before adding candidate fields such as score or associationScore.
References
- No additional runtime references are required; keep the import package limited to this file and the bundled scripts in
scripts/.
版本历史
- 11c74d6 当前 2026-07-19 09:39
