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.
npx agentmods add skills/extracurricular-ai/codex-rewind/code-review-testingnpx skills add extracurricular-ai/codex-rewind --skill code-review-testinggit clone --depth 1 https://github.com/extracurricular-ai/codex-rewindWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/extracurricular-ai/codex-rewind/code-review-testing)<a href="https://agentmods.dev/skills/extracurricular-ai/codex-rewind/code-review-testing"><img src="https://agentmods.dev/badge/skills/extracurricular-ai/codex-rewind/code-review-testing.svg" alt="Measured on agentmods" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00008 | $0.00122 |
| Opus 5 | $0.00004 | $0.00061 |
| Sonnet 5 | $0.00002 | $0.00024 |
| Haiku 4.5 | $0.00001 | $0.00012 |
Grade A, and why
code-review-testing 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 3d ago.
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.
This is a copy
100% identical to code-review-testing — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
What it actually says
For agent changes prefer integration tests over unit tests. Integration tests are under core/suite and use test_codex to set up a test instance of codex.
Features that change the agent logic MUST add an integration test:
- Provide a list of major logic changes and user-facing behaviors that need to be tested.
If unit tests are needed, put them in a dedicated test file (*_tests.rs). Avoid test-only functions in the main implementation.
Check whether there are existing helpers to make tests more streamlined and readable.
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.
- 3d ago First seen · 15 lines · 8 tokens per session scan A 7722784fda70
code-review-testing is a skill published in the GitHub repository extracurricular-ai/codex-rewind (44 stars, last pushed 7d ago), licensed Apache-2.0. It adds 8 tokens to every session and 122 once invoked, about $0.0000 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to code-review-testing, differing in 0 lines, and is treated as a copy.
Other skills, from other repositories
fast-resume
Search local coding-agent session history and identify safe resume commands. Use when the user asks to find, inspect, continue, or recover previous work from Claude Code, Codex, Pi, or another agent indexed by fast-resume.
intuitive-preflight
Turn a vague task, plan, issue, or "LGTM/go ahead" request into an approval-ready preflight contract before implementation starts. Use when the user wants prompt preflight, clearer scope, non-goals, context package, acceptance criteria, definition of done, verification, stop gates, the exact execution command, or…
intuitive-squash
Squash local GSD or agent-generated commit history into a clean, reviewable story while preserving important fixes. Use when the user asks to squash commits, clean git history, compress phase commits, prepare a branch before PR, compare aggressive vs moderate squash options, or preserve hotfix/security commits during…
cross-review
Challenge an existing agent proposal through a small bounded set of independent review perspectives, then judge the findings into one simpler or more defensible recommendation. Use immediately after an agent proposes a solution when the user asks whether there is a simpler approach, wants a second opinion or other…
intuitive-refactor
Refactor and cleanup router for known code/module/API seams, stale surfaces, compatibility shims, architecture cleanup targets, changed-code quality review, oversized modules, repeated cleanup campaigns, and recurring whole-repo architecture maintenance goals. Use this when the user names a concrete seam, wants…
intuitive-shape
Shape a raw product or project idea into a bounded decision before planning or implementation. Use when deciding whether an idea deserves a bet, setting an appetite, comparing candidate bets under finite capacity, cutting scope, exposing rabbit holes and no-gos, or choosing BET, RESEARCH, RESHAPE, or PASS. This skill…