release-candidate-prep

A release checklist and workflow for preparing a specific OpenAI Agents Python release candidate in a separate Git worktree. A worktree is an additional checkout of the same repository used for isolated changes.

In plain words
What is it for?
Use it when explicitly preparing a versioned release candidate from the exact origin/main branch, freezing the released API contract, and reviewing the final release state.
Why use it?
It provides readiness checks and keeps release changes separate from the developer's main checkout while creating one reviewed release commit.

Skill for Claude CodeCodex

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/openai/openai-agents-python/release-candidate-prep
Any agent
npx skills add openai/openai-agents-python --skill release-candidate-prep
Clone the repo
git clone --depth 1 https://github.com/openai/openai-agents-python

Made for: Claude Code, Codex.

Per session 87 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,771 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00087 $0.03771
Opus 5 $0.00044 $0.01886
Sonnet 5 $0.00017 $0.00754
Haiku 4.5 $0.00009 $0.00377

Measured 2d ago against content hash 2d506f9785f7, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

release-candidate-prep scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.

The scan reads SKILL.md. This mod also ships 2 executable files (scripts/prepare.py, scripts/test_prepare.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

.agents/skills/release-candidate-prep/SKILL.md · 179 lines

How it starts

The opening of the file, as written. The whole thing — 179 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Release Candidate Preparation

Use this skill only when the user explicitly invokes $release-candidate-prep and supplies a release version without a leading v, for example VERSION=0.20.1. This skill replaces the removed GitHub Actions release-PR creator with a reviewed local workflow.

Non-negotiable boundaries

  • Treat explicit invocation as authorization to fetch origin/main, create one dedicated detached release worktree, run branch-free release-readiness gates there, create or replace the local release/v<version> in that worktree only after those gates pass, update the three release-owned files, and create one local commit. If the branch already exists locally or remotely, the required final local state is still exact current origin/main plus only the new release commit; an existing local branch may be replaced only when it is not checked out in another worktree.
  • Keep the user's source checkout on its existing clean main commit. Do not fast-forward it, switch its branch, or materialize release files there. Leave the dedicated release worktree in place for green handoff, blocked review, or recoverable failure.
  • Never push, open or edit a pull request, add labels or milestones, create a release, or otherwise mutate GitHub. Never run gh.
  • Own exactly pyproject.toml, uv.lock, and tests/fixtures/released_api_contract.json. Runtime, documentation, workflow, or other repository changes must land on main before release preparation.
  • Do not stash, delete, overwrite or remove an existing worktree, or work around unrelated local changes. Fail before branch creation when the initial checkout is dirty or is not on main, the dedicated worktree is not clean and detached at refreshed origin/main, an existing local release branch is checked out in another worktree, the prospective packaged-contract gate fails after the allowed dependency-bootstrap recovery, the planning review blocks, or origin/main advances after those gates run.
  • Treat $final-release-review as the controlling release checker, not only as a report generator. Its planning gate must be green before branch creation, and its final-candidate gate must inspect the materialized worktree and be green before PR-ready handoff. Any candidate content, commit, or base change invalidates the previous green result.
  • Remove inherited OPENAI_API_KEY from every child command. Release preparation does not require a live OpenAI API request.
  • Stop after the local commit, final release review, and copy-ready handoff. The user owns the push and pull-request creation.

Read the full file on GitHub · 179 lines

Files

What ships with it

2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 2d ago First seen · 179 lines · 87 tokens per session scan A 2d506f9785f7

Subscribe to this mod's changes

release-candidate-prep is a skill published in the GitHub repository openai/openai-agents-python (29,075 stars, last pushed 4d ago), licensed MIT. It adds 87 tokens to every session and 3,771 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.