DevSpace Manual QA Setup
Waishnav/devspace
Prepares the current DevSpace checkout or worktree for isolated local manual QA, covering QA state seeding, UI asset builds and snapshot resets.
Carry implementation through an isolated worktree and local handoff.
$ npx skills add openai/openai-agents-python --skill implementation-kickoff -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install openai/openai-agents-python implementation-kickoff --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-kickoff .claude/skills/implementation-kickoff && 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-kickoff" agent skill from https://github.com/openai/openai-agents-python/tree/main/.agents/skills/implementation-kickoff into .claude/skills/implementation-kickoff/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "implementation-kickoff", 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-kickoffType 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-kickoff -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install openai/openai-agents-python implementation-kickoff --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-kickoff .agents/skills/implementation-kickoff && 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-kickoff" agent skill from https://github.com/openai/openai-agents-python/tree/main/.agents/skills/implementation-kickoff into .agents/skills/implementation-kickoff/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "implementation-kickoff", 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-kickoff -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install openai/openai-agents-python implementation-kickoff --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-kickoff .cursor/skills/implementation-kickoff && 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-kickoff" agent skill from https://github.com/openai/openai-agents-python/tree/main/.agents/skills/implementation-kickoff into .cursor/skills/implementation-kickoff/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "implementation-kickoff", 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-kickoff--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-kickoff -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install openai/openai-agents-python implementation-kickoff --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-kickoff .gemini/skills/implementation-kickoff && 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-kickoff" agent skill from https://github.com/openai/openai-agents-python/tree/main/.agents/skills/implementation-kickoff into .gemini/skills/implementation-kickoff/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "implementation-kickoff", 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-kickoffInstalls 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-kickoff -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-kickoff .github/skills/implementation-kickoff && 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-kickoff" agent skill from https://github.com/openai/openai-agents-python/tree/main/.agents/skills/implementation-kickoff into .github/skills/implementation-kickoff/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "implementation-kickoff", 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-kickoff -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-kickoff --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-kickoff .opencode/skills/implementation-kickoff && 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-kickoff" agent skill from https://github.com/openai/openai-agents-python/tree/main/.agents/skills/implementation-kickoff into .opencode/skills/implementation-kickoff/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "implementation-kickoff", 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-kickoffCarry implementation through an isolated worktree and local handoff.
Implementation Kickoff is an agent skill from openai/openai-agents-python, published by the product's own GitHub organization. Carry implementation through an isolated worktree and local handoff. Use only when this skill is explicitly invoked.
Its SKILL.md is about 2.9k tokens, which your agent loads only when the skill is triggered. The skill folder holds 5 other files, including scripts (for example `agents/openai.yaml`, `scripts/test_validate_handoff.py` and `scripts/validate_handoff.py`).
It sits in Development, covering Git worktrees. It works with OpenAI. The repository describes itself as: A lightweight, powerful framework for multi-agent workflows. The licence is MIT.
8 steps, taken from the step headings in SKILL.md.
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 2 files in scripts/ (Python), which the agent can run.
Shell commands in SKILL.md call:
gitpythonFrom the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md. Its commands use git, which can reach the network depending on how they are called.
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 Kickoff loads about 2.9k tokens when it runs. Until then it costs about 35 tokens; SKILL.md has 1,608 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). 1,608 words, ~2,910 tokens.
.claude/skills/implementation-kickoff/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.Use this skill as the explicit transition from an agreed implementation scope to isolated execution. Keep the user's original checkout and existing branches unchanged, and finish with a clean local branch that is ready for the user to push.
Record the original requirement, success criteria, intended target (origin/main unless the user states otherwise), task-owned paths, compatibility boundary, intentionally unsupported cases, and required repository skills. For a multi-step task, create and maintain the repository's required ExecPlan. An ExecPlan, review packet, ledger, trace, or temporary report is operational-only by default even when repository policy requires creating it; do not add it to the shipped-path manifest unless the original requirement or repository policy explicitly makes that exact path a committed deliverable.
If the current directory is a worktree previously created for this same task in the current conversation, resume it. Otherwise, continue from the user's current checkout only long enough to create a new worktree.
origin main. If the fetch fails, stop rather than claiming a stale ref is current.origin/main commit.git worktree list; never reuse or delete a collision.git worktree add --detach <worktree> origin/main and perform all subsequent implementation work there.Do not create the final branch yet. A detached worktree makes the eventual $pr-draft-summary branch suggestion authoritative and prevents temporary naming from becoming accidental output.
Keep the task diff uncommitted through implementation, focused tests, formatting, and review fixes. Track new files explicitly because ordinary diff statistics omit untracked files. Maintain one canonical shipped-path manifest separately from operational artifacts and require a concrete deliverable reason for every path in it. Use the applicable repository skills and references, including $implementation-strategy before user-facing or runtime changes.
When the task can be decomposed without temporarily breaking a supported contract, implement one narrow end-to-end behavior slice at a time and run its focused test before adding the next slice. Do not force cross-cutting migrations or atomic compatibility changes into artificial slices that cannot remain valid independently.
Do not create checkpoint commits. If an external interruption requires extra protection, leave the dedicated worktree intact or use a clearly named temporary stash; restore the changes before continuing and do not treat the stash as a deliverable.
When the user asks to complete another author's pull request:
origin/main; do not derive the final branch from the contributor branch and do not preserve its intermediate commit topology.Co-authored-by trailers, linked issues, and the original intent that the replacement must preserve.After implementation, focused tests, and formatting are stable, fetch origin main again. If it advanced:
origin/main. With no task commits, this updates the empty local commit range to the new base.Record this observed origin/main commit as the final-base candidate. Do not call an older base "latest" merely because its changes appear unrelated.
Run applicable completion gates against the complete task-owned diff on the final-base candidate. Apply formatting and safe hook-equivalent normalization before review, including generated-file provenance checks where relevant. Use $implementation-final-review to select lightweight, ordinary, or high-risk review; supply all task-owned untracked file contents as well as tracked changes. Only high-risk review requires review_state.py --complete-diff-output <complete.diff> and the strict packet/ledger protocol. Follow the selected procedure's evidence and invalidation rules.
Run $code-change-verification after clean review whenever its SDK eligibility rules apply. A lightweight review exemption does not waive an otherwise required SDK verification stack. Repo-meta work uses its applicable skill and focused checks. Do not create the branch or commit while required review, verification, or evidence remains incomplete.
Invoke $pr-draft-summary only after review and verification apply to the final content. Give it a self-contained packet containing the original requirement, implementation scope contract, important decisions and intent, complete changed-path inventory including untracked files, final diff and statistics, compatibility notes, issue references, and takeover provenance.
The worktree is intentionally detached. Tell $pr-draft-summary to treat the current branch value HEAD as "no branch yet" and require a concrete unused branch-name suggestion; never accept HEAD as the suggestion. The description must explain the complete final change and its motivation, not only the last review fix.
For a takeover, begin the description with prose such as This pull request supersedes #<number> and .... Preserve any separate issue-closing line only when the final implementation actually resolves that issue.
If the diff, scope, base, behavior claim, issue relationship, or provenance changes after generation, regenerate the entire PR handoff.
Fetch origin main once more immediately before creating the branch. If it differs from the final-base candidate, return to section 4 and replay onto the new base. Apply the selected review tier's base-change rules in $implementation-final-review; only high-risk work uses the verified base-advance closure in high-risk-review.md step 20. Recheck relevant upstream dependencies and tooling before retaining review evidence. Rerun applicable final verification on the new base and regenerate the PR handoff; obtain affected independent re-review whenever the selected tier requires it. Once stable:
$pr-draft-summary for the next available numeric suffix and regenerate the handoff before creating a colliding branch.Co-authored-by: Name <email>, retain distinct valid co-author trailers from the imported commits, and deduplicate identities.Branch creation and committing identical content are repository bookkeeping and do not invalidate clean content review. If a hook or manual fix changes task content, stop, classify the change under $implementation-final-review, and rerun every invalidated gate and $pr-draft-summary before replacing or amending the commit.
Run python .agents/skills/implementation-kickoff/scripts/validate_handoff.py --repo <worktree> --base <final-base> --expected-branch <branch> --shipped-path-manifest <manifest>. For a takeover, also pass --required-trailer-email <verified-email> for each identity that must be credited. The shipped-path manifest must be a finite regular file whose type and content are read from one opened descriptor. It contains one exact repository-relative shipped path per line and excludes operational artifacts.
Independently confirm that the committed diff has the reviewed content fingerprint when final review supplied one. The validator checks Git topology and repository cleanliness; it does not replace semantic review or fingerprint verification.
Leave the worktree in place. Report the worktree path, final observed base commit, branch, commit SHA and subject, verification results, review status, PR title and description, and whether takeover provenance was included. Treat the worktree path and validator output as local diagnostics: never include them in the PR title, PR description, or other copy-ready external text. State explicitly that nothing was pushed and no pull request was created.
© 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 3 other files (scripts) in .agents/skills/implementation-kickoff 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 Kickoff 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 Kickoff this skillopenai/openai-agents-python | 30k | — | ~2.9k | Automated safety check: Pass | MIT | |
| DevSpace Manual QA SetupWaishnav/devspace | 5.2k | — | ~440 | Automated safety check: Pass | MIT | |
| Nagentdavidondrej/skills | 4.1k | — | ~1.7k | Automated safety check: Notes | MIT | |
| Live Extension UI Automationqixing-jk/all-api-hub | 4.9k | — | ~2.6k | Automated safety check: Pass | AGPL-3.0 | |
| Worktree PortsFranciscoMoretti/chat-js | 1.2k | — | ~231 | Automated safety check: Notes | Apache-2.0 | |
| Audit Depsgarfiec/Librechat-Mobile | 110 | — | ~2.4k | Automated safety check: Notes | MIT |
Waishnav/devspace
Prepares the current DevSpace checkout or worktree for isolated local manual QA, covering QA state seeding, UI asset builds and snapshot resets.
davidondrej/skills
Launch a new bb worker thread with the right project, model, worktree, and task brief.
qixing-jk/all-api-hub
Control, debug, and test the live dev browser extension UI (Options, Popup, Sidepanel) via CDP with persistent login states and accounts.
FranciscoMoretti/chat-js
Discover and use stable per-app ports assigned to a local monorepo worktree.
garfiec/Librechat-Mobile
Audit open dependabot PRs in this repo. An agent skill from garfiec/Librechat-Mobile.
kortix-ai/suna
Drive OpenAI's Codex CLI (codex exec) as a non-interactive coding sub-agent from inside Claude Code.
openai/openai-agents-python
Review completed implementation changes before final verification.
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.
Works with
Categories
Carry implementation through an isolated worktree and local handoff. Implementation Kickoff is an agent skill from openai/openai-agents-python, published by the product's own GitHub organization. Carry implementation through an isolated worktree and local handoff.
Implementation Kickoff fits situations like: tasks that involve Git worktrees.
Run `npx skills add openai/openai-agents-python --skill implementation-kickoff -a claude-code`. Or copy the skill folder (.agents/skills/implementation-kickoff in openai/openai-agents-python) into .claude/skills/implementation-kickoff in your project. Claude Code loads it when a task matches its description.
Run `npx skills add openai/openai-agents-python --skill implementation-kickoff -a codex`. Or copy the skill folder (.agents/skills/implementation-kickoff in openai/openai-agents-python) into .agents/skills/implementation-kickoff 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-kickoff -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-kickoff, .gemini/skills/implementation-kickoff, .github/skills/implementation-kickoff and .opencode/skills/implementation-kickoff in your project.
Going by SKILL.md and its folder, Implementation Kickoff needs Python for the scripts in its folder and the command-line tools its instructions call (git and python). Our summary lists: Python 3.
SKILL.md contains no URLs. Its commands use git, which can reach the network depending on how they are called. 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 Kickoff is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 2.9k tokens (SKILL.md is roughly 12k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with Implementation Kickoff: DevSpace Manual QA Setup (Waishnav/devspace, 5.2k stars), Nagent (davidondrej/skills, 4.1k stars), Live Extension UI Automation (qixing-jk/all-api-hub, 4.9k stars) and Worktree Ports (FranciscoMoretti/chat-js, 1.2k 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.