PR Design Doc
OpenHands/OpenHands
For a non-trivial pull request, write a self-contained HTML design doc under the temporary .pr/ directory and link a visibility-appropriate preview in the PR description, so maintainers grasp the…
Review completed implementation changes before final verification.
$ npx skills add openai/openai-agents-python --skill implementation-final-review -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install openai/openai-agents-python implementation-final-review --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/openai/openai-agents-python.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/implementation-final-review .claude/skills/implementation-final-review && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "implementation-final-review" agent skill from https://github.com/openai/openai-agents-python/tree/main/.agents/skills/implementation-final-review into .claude/skills/implementation-final-review/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "implementation-final-review", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/openai/openai-agents-python/tree/main/.agents/skills/implementation-final-reviewType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add openai/openai-agents-python --skill implementation-final-review -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install openai/openai-agents-python implementation-final-review --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/openai/openai-agents-python.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.agents/skills/implementation-final-review .agents/skills/implementation-final-review && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "implementation-final-review" agent skill from https://github.com/openai/openai-agents-python/tree/main/.agents/skills/implementation-final-review into .agents/skills/implementation-final-review/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "implementation-final-review", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add openai/openai-agents-python --skill implementation-final-review -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install openai/openai-agents-python implementation-final-review --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/openai/openai-agents-python.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.agents/skills/implementation-final-review .cursor/skills/implementation-final-review && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "implementation-final-review" agent skill from https://github.com/openai/openai-agents-python/tree/main/.agents/skills/implementation-final-review into .cursor/skills/implementation-final-review/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "implementation-final-review", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/openai/openai-agents-python.git --path .agents/skills/implementation-final-review--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add openai/openai-agents-python --skill implementation-final-review -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install openai/openai-agents-python implementation-final-review --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/openai/openai-agents-python.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.agents/skills/implementation-final-review .gemini/skills/implementation-final-review && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "implementation-final-review" agent skill from https://github.com/openai/openai-agents-python/tree/main/.agents/skills/implementation-final-review into .gemini/skills/implementation-final-review/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "implementation-final-review", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install openai/openai-agents-python implementation-final-reviewInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add openai/openai-agents-python --skill implementation-final-review -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/openai/openai-agents-python.git skills-src && mkdir -p .github/skills && cp -r skills-src/.agents/skills/implementation-final-review .github/skills/implementation-final-review && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "implementation-final-review" agent skill from https://github.com/openai/openai-agents-python/tree/main/.agents/skills/implementation-final-review into .github/skills/implementation-final-review/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "implementation-final-review", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add openai/openai-agents-python --skill implementation-final-review -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install openai/openai-agents-python implementation-final-review --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/openai/openai-agents-python.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.agents/skills/implementation-final-review .opencode/skills/implementation-final-review && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "implementation-final-review" agent skill from https://github.com/openai/openai-agents-python/tree/main/.agents/skills/implementation-final-review into .opencode/skills/implementation-final-review/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "implementation-final-review", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
implementation-final-reviewReview completed implementation changes before final verification.
Implementation Final Review is an agent skill from openai/openai-agents-python, published by the product's own GitHub organization. Review completed implementation changes before final verification. Use when repository policy requires independent review or the user explicitly requests it.
Its SKILL.md is about 2k tokens, which your agent loads only when the skill is triggered. The skill folder holds 10 other files, including scripts and reference files (for example `agents/openai.yaml`, `references/high-risk-review.md` and `references/reviewer-brief.md`).
It sits in Development. It works with OpenAI. The repository describes itself as: A lightweight, powerful framework for multi-agent workflows. The licence is MIT.
Read from SKILL.md and the folder at commit 71c2da4. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Ships 4 files in scripts/ (Python), which the agent can run.
From the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Implementation Final Review loads about 2k tokens when it runs, and up to ~21k if it reads all its reference files. Until then it costs about 46 tokens; SKILL.md has 999 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.
The full file from openai/openai-agents-python at commit 71c2da4, republished under its MIT licence (© openai). 999 words, ~1,972 tokens.
.claude/skills/implementation-final-review/SKILL.md (or your agent's skills folder). This skill also uses 7 other files; get the full folder from GitHub.Review the original requirement and complete task diff, including committed, staged, unstaged, and task-owned untracked files. Use the intended target's merge base for patch ownership and the latest release separately when released compatibility matters. Apply the finding threshold and supported-scope rules in AGENTS.md.
Classify the complete change by its semantic impact, not its line count, extension, or location. Record the tier and a short reason in existing working notes; do not create a separate classification report.
| Tier | Boundary | Required review |
|---|---|---|
| Lightweight | Only spelling, comments, or formatting; no change to execution, public contracts, test expectations, configuration, or documented meaning. | Self-check the complete diff and run applicable focused checks. Independent review is optional. |
| Ordinary | Local behavior changes within an established contract, ordinary test additions, or behavioral documentation without a high-risk boundary change. | One independent reviewer in a fresh context. Use the procedure below. |
| High risk | Changes to security, credentials, sensitive-data handling, trust, persistence/resume, durable state, concurrency/cancellation/shared lifecycle ownership, released compatibility, package/runtime exports, protocol ownership, or cross-provider lifecycle; also any review cycle with a validated P0/P1. | Two independent reviewers with complementary specialties. Read high-risk-review.md, which owns the strict protocol and final-evidence rules. |
A one-line condition fix is at least ordinary. Public annotations and schema-generating types can change contracts. Test deletion or changed expectations, CI/build configuration, and policy changes are not lightweight merely because they do not edit runtime files. An uncertainty about high-risk impact must be resolved before accepting an ordinary clean review; escalate when the affected boundary requires it. Do not downgrade a cycle after a validated P0/P1 just because the immediate fix is small.
Planning, investigation, and report-only tasks do not start this implementation workflow. Repo-meta work uses the applicable skill's focused validation. When implementing changes to decision-making guidance, perform realistic scenario checks and an independent pass rather than an SDK runtime review packet. Report-only assessments may inspect existing review/scenario evidence; they do not automatically commission another implementation review. Editorial documentation follows the repository's documentation verification tiers.
Finish affected tests and any formatting or safe hook-equivalent normalization that can change the task diff. Reuse successful focused checks for unchanged content. Do not start broad final verification until review is clean.
Give one reviewer the original request, a short scope contract, target/base/head identifiers, task-owned paths, complete diff including new-file contents, relevant architecture references, and exact focused-check commands and results. Record the reviewed content in a saved diff plus new-file snapshots or a content fingerprint, so later comparison can establish what was reviewed. Keep temporary evidence outside shipped deliverables. scripts/review_state.py is available when useful, but the strict JSON packet, component ledger, evidence IDs, and verification receipts are not required for ordinary review.
Launch one independent agent with no inherited implementer conversation (fork_turns: "none" when supported). Do not supply intended findings, previous reviewer conclusions, or proposed fixes. The reviewer inspects the complete diff and relevant surrounding source, verifies the scope contract rather than rerunning implementation strategy, and returns the reviewed scope, concrete actionable findings, and remaining uncertainty. A bare approval without inspected scope is insufficient; no fixed JSON schema is required.
The reviewer performs one read-only pass, does not edit, recursively delegate review, or run broad suites. Focused non-mutating probes are allowed only within existing execution and credential permissions. Keep task content fixed while review runs and use event-driven waits within the host's supported limits. Use wait time for independent work that cannot change reviewed content.
Validate findings against supported behavior and fix them as one batch. Update strategy only when the contract or implementation shape changes. Rerun affected checks and obtain an independent review of the changed content and its relevant boundaries before accepting completion. Review the complete resulting task diff when scope or cross-cutting assumptions changed. Escalate to the high-risk procedure if a changed boundary or validated P0/P1 requires it; an ordinary verdict does not substitute for its required pair.
Preserve a compact count and unresolved-root summary in existing task notes across pauses and compaction. The initial cycle allows up to six reviewed revisions, and concrete feedback after a completed handoff starts a two-revision cycle. These are caps, not targets. On escalation, carry consumed revisions and unresolved root causes into the high-risk handoff; record the remaining cycle budget and give the strict ledger only that remainder. Ordinary verdicts earn no high-risk clean credit. If no budget remains, obtain a concrete user decision before another dispatch. Infrastructure retries on unchanged content do not consume a revision. If repeated findings expose the same design problem, apply the repository complexity-reset rule instead of adding conditions indefinitely. Ask for a concrete scope/design decision when progress needs one or the budget is exhausted; otherwise continue autonomously through fixes, review, verification, and handoff.
Compare final task content with the recorded reviewed content. Changed behavior, expectations, contracts, or dependencies requires affected independent re-review. A demonstrably spelling/comment/formatting-only delta can retain prior review after self-check; do not extend that exemption to executable rewrites, public annotations, or behavioral prose. Committing or staging identical content does not invalidate review. A changed base requires checking the upstream delta and integration; if relevant source or tooling changed, or impact is uncertain, obtain affected re-review. Retain review only with recorded evidence of unchanged task behavior and unaffected dependencies.
Run every applicable final verification gate on the final content, using $code-change-verification for eligible SDK changes and documentation tiers for docs. A lighter review does not waive SDK checks. Preserving review after a formatting-only edit does not grant final-stack credit for changed content; follow the verification skill's final-content requirements. Report completion only when review and verification apply to the delivered state, then run $pr-draft-summary when required. If an independent reviewer is unavailable, report the missing review explicitly; self-review cannot satisfy the ordinary or high-risk gate.
Read high-risk-review.md only for high-risk work. It uses reviewer-brief.md and the existing scripts/review_state.py and scripts/review_protocol.py helpers. Do not prepare their packets, receipts, or component inventories for a lightweight or ordinary change.
© openai, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
SKILL.md and 7 other files (scripts, references) in .agents/skills/implementation-final-review of openai/openai-agents-python.
Open the folder on GitHubat commit 71c2da4
We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders. This page covers the copy in openai/openai-agents-python, which our catalogue first saw on October 7, 2026.
Implementation Final Review next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Implementation Final Review this skillopenai/openai-agents-python | 30k | — | ~2k | Automated safety check: Pass | MIT | |
| PR Design DocOpenHands/OpenHands | 90k | — | ~2.4k | Automated safety check: Pass | MIT | |
| Get API Docs with chubandrewyng/context-hub | 14k | 2 repos | ~775 | Automated safety check: Pass | MIT | |
| Open Code Review CLIalibaba/open-code-review | 44k | — | ~3.1k | Automated safety check: Pass | Apache-2.0 | |
| Codexskills-directory/skill-codex | 1.5k | 3 repos | ~1.8k | Automated safety check: Pass | MIT | |
| Changeset Validationopenai/openai-agents-js | 3.9k | — | ~607 | Automated safety check: Pass | MIT |
OpenHands/OpenHands
For a non-trivial pull request, write a self-contained HTML design doc under the temporary .pr/ directory and link a visibility-appropriate preview in the PR description, so maintainers grasp the…
andrewyng/context-hub
Fetches current documentation for third-party APIs and SDKs with the chub CLI before the agent writes code against them, instead of relying on remembered API shapes.
alibaba/open-code-review
Runs the ocr command-line tool to review Git changes, a commit or a branch comparison with an AI model, returning line-level comments and optionally applying fixes.
skills-directory/skill-codex
A skill your agent uses when the user asks to run Codex CLI (codex exec, codex resume) or references OpenAI Codex for code analysis, refactoring, or automated editing
openai/openai-agents-js
Validate changesets in openai-agents-js using LLM judgment against git diffs (including uncommitted local changes).
Waishnav/devspace
Prepares the current DevSpace checkout or worktree for isolated local manual QA, covering QA state seeding, UI asset builds and snapshot resets.
openai/openai-agents-python
Audit or fix sensitive-data exposure in Python SDK diagnostics, exceptions, logging, and telemetry.
openai/openai-agents-python
Assess a Python SDK release candidate or release plan against the previous release and recommend ship or block.
openai/openai-agents-python
Prepare a local Python SDK release candidate in a dedicated worktree.
openai/openai-agents-python
Run the required final formatting, lint, type, and test checks after eligible SDK changes pass review.
openai/openai-agents-python
Analyze logs and source from a completed manual examples run.
openai/openai-agents-python
Carry implementation through an isolated worktree and local handoff.
Works with
Categories
Review completed implementation changes before final verification. Implementation Final Review is an agent skill from openai/openai-agents-python, published by the product's own GitHub organization. Review completed implementation changes before final verification.
Implementation Final Review fits situations like: repository policy requires independent review; the user explicitly requests it.
Run `npx skills add openai/openai-agents-python --skill implementation-final-review -a claude-code`. Or copy the skill folder (.agents/skills/implementation-final-review in openai/openai-agents-python) into .claude/skills/implementation-final-review in your project. Claude Code loads it when a task matches its description.
Run `npx skills add openai/openai-agents-python --skill implementation-final-review -a codex`. Or copy the skill folder (.agents/skills/implementation-final-review in openai/openai-agents-python) into .agents/skills/implementation-final-review in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add openai/openai-agents-python --skill implementation-final-review -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/implementation-final-review, .gemini/skills/implementation-final-review, .github/skills/implementation-final-review and .opencode/skills/implementation-final-review in your project.
Going by SKILL.md and its folder, Implementation Final Review needs Python for the scripts in its folder. Our summary lists: Python 3.
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.
Implementation Final Review is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 2k tokens (SKILL.md is roughly 7.9k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 19k tokens, read only when the agent opens those files.
Skills that share tags, products or a category with Implementation Final Review: PR Design Doc (OpenHands/OpenHands, 90k stars), Get API Docs with chub (andrewyng/context-hub, 14k stars), Open Code Review CLI (alibaba/open-code-review, 44k stars) and Codex (skills-directory/skill-codex, 1.5k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
openai (a GitHub organization, an official publisher) maintains it in openai/openai-agents-python, which has 29,873 GitHub stars. The repository holds 14 skills in this directory. The repository was last updated on October 7, 2026.
Source: openai/openai-agents-python on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.