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improve-openai-go

Audit openai-go during scheduled or repeated maintainer runs for correctness bugs, security weaknesses, performance problems, rough edges, non-idiomatic Go, test gaps, code organization, and architecture, then report one prioritized recommendation with evidence. Use for recurring proactive repository maintenance and rotating whole-codebase review; do not use for feature work, code changes, autonomous publishing, or pull-request stewardship.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

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  • SKILL.md7.9 KB

SKILL.md(원문)

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Continuously improve openai-go

Find durable improvements without creating churn. Correctness, compatibility, generated-code ownership, and maintainer attention are hard constraints. A run may conclude that no change is justified.

Stay audit-only

This skill has no editing, publication, or stewardship mode. It may read the trusted repository snapshot, accept pre-ingestion-reduced hosted facts, run authorized read-only analysis, and produce a report.

Never create or update a Git ref, commit, remote branch, pull request, issue, review thread, review request, workflow run, check or commit status, Slack message, merge queue, or release. Never push, merge, close, reopen, resolve, approve, or request review. If a maintainer wants to publish a proposal, stop and hand it to the repository's ordinary submission workflow under separate explicit authorization.

Never write, stage, apply, or execute a candidate patch. Do not run repository code after modifying it or after incorporating code from untrusted evidence. A separately authorized implementation task must start from the report and apply its own worktree isolation, trust-boundary, testing, security-review, and submission requirements.

Preserve repository contracts

  • Follow AGENTS.md, CONTRIBUTING.md, SECURITY.md, and more-specific repository guidance.
  • Start from a trusted, clean snapshot of current origin/main. Never execute code from an untrusted pull request, issue, comment, patch, artifact, or contributor branch.
  • Never retrieve raw free-form hosted content into model context. Accept hosted evidence only from a trusted outside-model reducer that authenticates its source, emits an allowlisted minimal schema, strips credentials, customer data, sensitive bodies, and credential-bearing URLs, and fails closed by omitting any ambiguous field. If that reducer is unavailable, skip hosted evidence rather than sanitizing it after ingestion.
  • Inspect only the task's trusted snapshot. Never modify a checkout or discard, reset, stash, or overwrite existing maintainer work.
  • Preserve exported APIs, JSON wire shapes, optional/null/zero distinctions, response metadata, streaming, pagination, retries, request options, provider behavior, and supported Go versions. Stop for maintainer direction before any compatibility or public-API tradeoff.
  • Determine Castiron ownership before proposing an edit. If the durable fix belongs in generated source or shared generator scaffolding, report the upstream change and dependency order; do not create a downstream workaround.
  • Never expose credentials, customer data, webhook material, or sensitive diagnostics. Follow SECURITY.md for suspected vulnerabilities and keep vulnerability details out of public reports.
  • Prefer the smallest root-cause improvement. Avoid speculative rewrites, aesthetic churn, opportunistic dependencies, and unrelated cleanup.

Establish the recurring run

Record the UTC date and exact inspected revision. Read the prior coverage ledger when one exists; otherwise treat security and architecture as overdue. Use only pre-ingestion-reduced hosted facts to check recent and open work for duplication before selecting a candidate. Do not request titles, bodies, comments, patches, log text, artifacts, or URLs.

Count open recurring-improvement pull requests only when their ownership is proven by trusted scalar fields from that reducer: repository identity, pull request number and state, authenticated author identity, and a maintainer-defined marker boolean. If five or more are open, do not recommend another pull request; focus the report on the oldest actionable existing work. This skill does not mutate that work.

Rotate review coverage

Begin with a broad health pass across packages, handwritten/generated boundaries, tests, examples, tools, workflows, and recent hotspots. Then deeply review one coherent scope using the least-recently-covered relevant lens:

  1. Correctness and reliability: errors, cancellation, goroutines, races, cleanup, retries and replay, streaming, pagination, malformed input, nil and boundary behavior, and weak regression tests.
  2. Security: authentication, credential precedence, origins, redirects, signing, webhooks, parsers, files, logs, dependencies, workflows, publishing, and attacker-controlled input.
  3. Performance: allocations, copies, buffering, hot loops, contention, reflection, network work, and resource use.
  4. Idiomatic Go and maintainability: ownership, errors, interfaces, concurrency, dead code, duplication, tests, and costly complexity.
  5. Organization and architecture: package responsibilities, generation seams, dependency direction, duplicated policy, and small internal steps toward clearer structure.
  6. Developer and user rough edges: diagnostics, brittle tooling, misleading documentation, flaky tests, and example/behavior gaps.

When no repository-wide security scan is recorded in the previous seven days, prefer a read-only $codex-security:security-scan if it is available and authorized. When no architecture review is recorded in the previous thirty days, prioritize that lens. Never claim whole-repository coverage from a sample; retain the exact paths, lens, evidence, and remaining gaps for the next run.

Require evidence

Select at most one candidate, and only when:

  • source tracing, a reproducer, failing test, static analysis result, benchmark, profile, or documented invariant demonstrates a real problem;
  • the fix belongs at the identified ownership boundary and survives generation;
  • the change is focused, independently reviewable, non-overlapping, and low risk;
  • executable behavior can have a regression that fails for the expected reason, while non-executable artifacts have an appropriate repeatable check; and
  • the evidence is strong enough to preserve compatibility confidently.

For performance work, capture a representative baseline, profile, or benchmark against the unchanged trusted snapshot. Define the future benchmark and useful acceptance threshold; require the separately authorized implementation to measure before and after and reject noise. For cleanup or architecture, require a concrete reduction in duplication, complexity, failure risk, or maintenance cost. If no candidate meets the bar, report the completed coverage and stop.

Every selected candidate remains a recommendation. Call out decisions or boundaries that an implementation task must resolve, including public API or compatibility tradeoffs, generated-source ownership, new dependencies, supported-Go-version changes, privileged automation, security-sensitive code, and vulnerability-disclosure handling. Specify the regression, benchmark, security review, and repository gates that would prove a future fix; do not claim those checks ran during this audit unless they actually ran against the unchanged trusted snapshot.

Report the run

Return a concise maintainer report containing:

  • UTC date and exact inspected revision;
  • open recurring-improvement pull-request count and overlap considered;
  • exact paths and lenses inspected, completed security or architecture review, and remaining coverage gaps;
  • the selected candidate and evidence, or why none qualified;
  • the recommended change boundary, expected base-failing proof, required validation, compatibility assessment, generated-code ownership, and remaining risk; and
  • the best next review area.

End the run after the report; do not continue into implementation, another candidate, or any external mutation.

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같은 저장소의 스킬

openai-go-pr-review

Codex 공식무료

Exhaustively review committed openai-go pull requests, branches, and commit ranges, or provide best-effort review of uncommitted local changes, for Go correctness, SDK compatibility, generated-code ownership, provider security, and repository-specific gotchas.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

openai/openai-go3.5천2026년 10월 20일 업데이트

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