Analyze CSV files with Python and get concise numerical summaries. The skill checks column structure before calculating requested aggregates, includes units when available, and explains assumptions when data is missing or incorrectly formatted.
Investigate runtime behavior that code review and normal tests cannot resolve. Plan controlled cases, disclose commands and effects for approval, then use temporary scripts to report observed results, comparison conditions, and supporting evidence.
Run final checks after reviewed SDK changes, covering dependency installation, builds, types, generated declarations, linting, tests, and formatting. The workflow requires every check to pass before the work is marked complete.
Update pnpm locally and align package.json with GitHub Actions settings. Check the published package and CI installation paths first, then record package integrity and pin the setup action to a specific commit.
Fix a small formatting bug in a credit note shell script while keeping the output label as credit and the amount positive. Run the specified targeted test and summarize the bug, fix, and verification command.
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.
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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.
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Guide for running tests in the openai-dotnet repository. Use this when asked to run, debug, or validate tests, or when writing new tests. Explains test modes (Playback, Record, Live), how to identify recorded vs non-recorded tests, environment variable configuration, and what to do when recordings are missing or stale.
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Guide for ingesting the latest OpenAI TypeSpec specification into the openai-dotnet SDK. Use this when asked to update or ingest OpenAI API specs, copy base TypeSpec files from upstream, fix client TSP compile errors, or run code generation for new API areas.
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Browse, inspect, and pick reusable CAD parts with the Bits & Bolts plugin.
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Set measurement units and grid preferences, then open the Parts Library when the user chooses Set up for Bits & Bolts or asks for onboarding.
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Score a repository's agentic legibility from repo-visible evidence only. Use when Codex needs to audit how easy a codebase is for coding agents to discover, bootstrap, validate, and navigate, especially for harness-engineering reviews, developer-experience audits, repo cleanup, or before/after comparisons after improving docs, tooling, or architectural constraints.
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Create, connect, list, and inspect MCP tunnel runtimes through the local tunnel-client plugin. Use when Codex needs to manage secure MCP tunnels with aliases and native tunnel-client runtime processes.
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Investigate customer-impacting OpenAI Ruby SDK defects and privately handled security risks, then dispatch at most five evidenced, independent fixes to isolated project worktrees.
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Assess an openai-guardrails-python GitHub issue or pull request as a maintainer. Use to verify the claimed need and practical impact, compare supported alternatives or competing approaches, separate code quality from repository readiness, recommend the maintainer action, and draft a copy-ready comment when evidence, changes, or closure should be requested.
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Review an openai-guardrails-python release plan or final release candidate against the previous remote tag, determine the compatible release type, audit runtime and packaging risk, inspect current CI, and produce an English ship-or-block report. Use for pre-release readiness checks, not ordinary PR review or implementation.
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Perform the repository's risk-tiered independent final review before implementation completion. Use only when explicitly invoked or when repository instructions require it after behavior-impacting implementation work; audit the complete task diff, supported contracts, lifecycle and security boundaries, complexity, and tests before final verification.
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Start and carry an explicitly invoked openai-guardrails-python implementation through a fresh isolated worktree and a local PR-ready handoff. Fetch the latest origin/main, keep task changes uncommitted, replay them onto the latest main before final review, run applicable verification and $implementation-final-review, use $pr-draft-summary to generate the complete PR draft and branch name, then create one clean local commit with takeover provenance when applicable. Use only when the user explicitly invokes this skill; never push, open a PR, or mutate GitHub.
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Choose compatibility-aware scope for runtime and API changes in openai-guardrails-python. Use before initial implementation and each review-feedback batch to decide whether to patch, reset the design, preserve compatibility, or reject unsupported cases.
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Create the required PR-ready summary block, branch suggestion, title, and draft description for openai-guardrails-python after runtime, tests, examples, build/test configuration, or behavior-impacting docs change.
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Run the mandatory verification stack when changes affect runtime code, tests, examples, or build and test behavior in the OpenAI Guardrails Python repository.
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Check the advertised PHP version from a URL or hostname.
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Check PHP2Shell patch status with local or server access.
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Inspect Android network captures and intercept HTTP calls with the Snap-O CLI for a selected device/socket. Use for request/response details, websocket events, API response overrides, mock responses, or delays with Python route handlers.
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