code-review-action: Skill for Claude Code

.agents/skills/ci-watch/SKILL.md

ci-watch is a skill for Claude Code, Codex from julien777z/code-review-action. It costs 63 tokens per session (1,133 once invoked), scanned A, a copy of ci-watch, MIT.

A workflow for monitoring a GitHub pull request, which is a proposed code change, until review feedback is handled and automated checks pass.

In plain words
What is it for?
It helps review pull requests, classify feedback, fix valid problems, push changes, and confirm that checks and review discussions are complete.
Why use it?
It removes the need to repeatedly check for delayed comments, investigate findings manually, and track which issues are still unresolved.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: installed under .agents/ (shared by several agents).

This is julien777z/code-review-action's own configuration. It tells Claude Code and Codex how to work on code-review-action itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything code-review-action configures →

Reuse

Borrowing it

Nothing to install: this file belongs to julien777z/code-review-action. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/julien777z/code-review-action/main/.agents/skills/ci-watch/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/julien777z/code-review-action

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for ci-watch

README.md
[![agentmods](https://agentmods.dev/badge/skills/julien777z/code-review-action/ci-watch/github.svg)](https://agentmods.dev/skills/julien777z/code-review-action/ci-watch)
Your own site
<a href="https://agentmods.dev/skills/julien777z/code-review-action/ci-watch"><img src="https://agentmods.dev/badge/skills/julien777z/code-review-action/ci-watch/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.

agentmods 80×15 button for ci-watch

Your own site · 80×15
<a href="https://agentmods.dev/skills/julien777z/code-review-action/ci-watch"><img src="https://agentmods.dev/badge/skills/julien777z/code-review-action/ci-watch.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 63 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,133 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin 100% copy Near-identical to another mod 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 5.1 $0.00063 $0.01133
Opus 5 $0.00032 $0.00566
Sonnet 5 $0.00013 $0.00227
Haiku 4.5 $0.00006 $0.00113

Measured 8d ago against content hash ed7650ef771e, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

ci-watch 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 8d 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.

Origin

This is a copy

100% identical to ci-watch — 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.

.agents/skills/ci-watch/SKILL.md · 46 lines

How it starts

The opening of the file, as written. The whole thing — 46 lines — stays where its author put it; the contents beside it link to each section on GitHub.

CI Watch

Monitor a pull request through the delayed-review window and act on valid feedback instead of merely reporting it.

Workflow

  1. Resolve the pull request from an explicit number or URL, or from the current branch and repository. If the current branch is the repository default branch and changes are needed, create a new work branch before editing; after making and verifying changes, commit, push, create a PR if one does not already exist for that branch, then poll CI for that PR. If the current non-default branch has no PR, inspect open PRs and local branch relationships; ask only if multiple candidates remain plausible.
  2. Record a baseline containing the head SHA, review submissions, conversation comments, inline review threads, resolution state, and latest finding timestamp. Prefer thread-aware GitHub reads so duplicate, outdated, and resolved findings are distinguishable.
  3. Check and investigate existing review threads, comments, and issue/PR conversation items as part of the baseline, not only new findings. Classify each unresolved or recently-updated item as legitimate, duplicate, already fixed, stale/outdated, ambiguous, or incorrect before deciding whether the watch can be quiet.
  4. Start a 15-minute quiet timer from the most recent finding, from the latest baseline item that still needs investigation, or from the baseline check when no findings exist.
  5. Poll every 30–60 seconds while checks are pending, failing, or review threads remain unresolved. If all GitHub checks are green and all review findings are resolved or outdated, treat the PR as merge-ready and stop the watch loop immediately; do not do extra quiet-window polling or a final boundary poll.
  6. On every existing, new, or updated finding:
    • Reset the quiet timer.
    • Read the cited code and relevant surrounding behavior.
    • Classify it as legitimate, duplicate, already fixed, stale/outdated, ambiguous, or incorrect.
    • Fix legitimate issues with the smallest behaviorally complete change.
    • Run focused checks proportional to the change.
    • Commit and push verified fixes to the PR branch promptly. Re-read remote state before pushing if the branch changed concurrently.
    • Resolve review threads that are fixed, stale/outdated, duplicates, false positives, not applicable, or otherwise incorrect; leave ambiguous or still-actionable threads unresolved.
  7. After every push, restart the 15-minute quiet timer from the push time and continue polling because new automated reviews may target the new commit.
  8. Stop the watch loop when the PR is ready to merge: either all available code-review bots approve or report no findings, or the only remaining review items are unactionable, false positives, stale/outdated, or otherwise incorrect and GitHub checks are green. For cleanup-only feedback, apply the counted-review-round completion rule:
    • A round counts only after every review/check for its head finishes, or after the full 15-minute quiet window expires and a boundary poll captures all findings available at that time. Never count a still-pending review before that boundary.
    • Stop after two consecutive counted review rounds (three at most) contain only code-simplification suggestions and no correctness bugs. Do not keep pushing cleanup solely to trigger another review round.
    • Fully investigate every finding in the final counted round and fix every legitimate one. If any correctness bug appears, reset the cleanup-only streak and review the resulting head under this rule.
    • Use the 15-minute quiet window only while checks/reviews are still not fully settled; do not apply it after the PR is green and merge-ready.
  9. After the watch loop stops in a merge-ready state, run the repo-local code-simplifier/code-simplify pass across the PR diff. Investigate and fix legitimate simplification or maintainability issues it finds, preserve unrelated changes, run focused checks, then commit and push any verified fixes.
  10. After the post-watch code-simplifier push, perform one final CI/review poll for the updated PR head. Apply the counted-review-round completion rule from step 8: a pending bot review is not a final result, so keep polling until it finishes or the full 15-minute quiet window expires and a boundary poll completes. Address legitimate new failures or findings with the same rules above; if no changes were made by the code-simplifier pass, do the final poll against the existing head.

Read the full file on GitHub · 46 lines

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. 8d ago First seen · 46 lines · 63 tokens per session scan A ed7650ef771e

Subscribe to this mod's changes

ci-watch is a skill published in the GitHub repository julien777z/code-review-action (2 stars, last pushed 4d ago), licensed MIT. It adds 63 tokens to every session and 1,133 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to ci-watch, differing in 0 lines, and is treated as a copy.

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