Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/victorGPT/vibeusagenpx agentmods add skills/victorgpt/vibeusage/pr-review-cycle-retroWrote 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/victorgpt/vibeusage/pr-review-cycle-retro)<a href="https://agentmods.dev/skills/victorgpt/vibeusage/pr-review-cycle-retro"><img src="https://agentmods.dev/badge/skills/victorgpt/vibeusage/pr-review-cycle-retro/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/victorgpt/vibeusage/pr-review-cycle-retro"><img src="https://agentmods.dev/badge/skills/victorgpt/vibeusage/pr-review-cycle-retro.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 5.1 | $0.00033 | $0.01198 |
| Opus 5 | $0.00016 | $0.00599 |
| Sonnet 5 | $0.00007 | $0.00240 |
| Haiku 4.5 | $0.00003 | $0.00120 |
Grade A, and why
pr-review-cycle-retro 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 10d 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.
How it starts
The opening of the file, as written. The whole thing — 123 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Codex Review Churn Analysis (PR Retrospective)
Overview
Explain why Codex Cloud review had to be re-run. Attribute causes to specific development stages, not just PR outcomes.
When to Use
- Multiple @codex review cycles on the same PR.
- The same feedback appears across successive Codex reviews.
- Follow-up fix PRs exist shortly after merge.
- You need stage-level causes (design / implementation / testing / review packaging / release).
When NOT to use:
- Human-review-only churn.
- Pure formatting or mechanical PRs.
Core Pattern
- Select: Find PRs with Codex review churn (comment -> code update -> Codex review).
- Isolate: Filter only Codex Cloud reviews and actionable feedback.
- Evidence: Collect a traceable chain (Codex feedback -> code change or follow-up fix).
- Classify: Assign primary + secondary stage causes.
- Abstract: Roll causes into a stable taxonomy.
- Aggregate: Summarize causes across frontend/backends.
- Prevent: Enforce the PR template risk-layer gate before any future @codex review.
Quick Reference
| Item | Rule |
|---|---|
| Codex cycle | Codex review comment -> code update -> new Codex review |
| Evidence | Codex comment + fix commit OR follow-up fix PR OR regression doc |
| Stage attribution | design / implementation / testing / review packaging / release |
| Mixed PR | record both frontend and backend impact |
| Noise guard | if Codex comments are generic, mark low-signal |
| Risk-layer gate | if any trigger matches, fill the addendum before @codex review |
Stage Taxonomy (Definition)
- Design: missing requirements, unclear acceptance criteria, privacy/exposure gaps, cross-endpoint invariants not specified.
- Implementation: logic errors, incomplete edge cases, inconsistent ordering/aggregation.
- Testing: missing regression/E2E/contract tests, no reproduction script.
- Review Packaging: PR lacks context, spec, evidence, or minimal repro for Codex to review well.
- Release/Integration: environment constraints (gateway, permissions, paths), deploy-time mismatches.
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.
- 10d ago First seen · 123 lines · 33 tokens per session scan A 86c48b2dd070
pr-review-cycle-retro is a skill published in the GitHub repository victorGPT/vibeusage (131 stars, last pushed 1mo ago), licensed MIT. It adds 33 tokens to every session and 1,198 once invoked, about $0.0002 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.
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