Skill catalog: missing find-prs and find-issues skills
@SamMorrowDrums ci sta già lavorando.
Dal 10/6/2026.
Valutazione
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Descrizione
Context
The github-mcp-server skill catalog exposes search_pull_requests and search_issues as raw tools, and bundles them inside higher-level skills like trace-history and prepare-release. There is no dedicated find-prs or find-issues skill — i.e. a small, focused skill whose contract is just "find PRs/issues matching these criteria, return a list".
Why this matters
Observed during an external evaluation harness (progressive-disclosure-evals) running model arms against the github-mcp-server skill catalog: when a task is "find recent PRs by author X" or "find issues mentioning Y", the model that browses the skill catalog reliably picks search_issues with type:pr qualifiers rather than search_pull_requests. Both go to the same /search/issues REST endpoint and are functionally equivalent, but the catalog lacks a discoverable "find-prs" entry point, so the model lands on the more generic search_issues path.
This is fine for correctness (it works) but it has two downstream effects:
- Evaluation rubrics that mention
search_pull_requestsas the expected tool now have to encode that-or-search_issuesequivalence themselves (we just shipped this as a schema change on our side). - Users / agents browsing the skill catalog see no obvious skill for the common "find PRs by author" workflow and have to either reach for
trace-history(which does more) or improvise withsearch_issues.
Ask
Consider adding two small skills:
find-prs— find pull requests matching author / repo / label / state / date / keyword criteria. Wrapssearch_pull_requests(orsearch_issues type:pr, doesn't matter which the implementation picks).find-issues— same shape for issues. Wrapssearch_issues type:issue.
These would be the obvious search-and-list entry points and would resolve the catalog-gap symptom described above.
Out of scope
I'm not asking you to change search_issues / search_pull_requests themselves, or to deprecate anything. This is purely about a discoverability gap in the higher-level skill layer.
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