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review-followup-example

review-followup-example is a skill for Claude Code, Codex from DGouron/review-flow. It costs 23 tokens per session (315 once invoked), scanned A, original, MIT.

An example workflow for a follow-up code review after earlier review comments have been addressed. It checks the original blocking issues, verifies the new commits, and looks for regressions.

In plain words
What is it for?
Use it to review a merge request again after changes, record the status of each earlier issue, list newly found problems, and decide whether the change is ready to merge. A merge request is a proposed code change submitted for review.
Why use it?
It gives a reviewer a compact way to confirm that requested fixes are real and that the fixes did not create new problems.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

not rated 44repo 3d ago A scan SkillSpector: pass 23 tokens original MIT

Good fit Use it to review a merge request again after changes, record the status of each earlier issue, list newly found problems, and decide whether the change is ready to merge. A merge request is a proposed code change submitted for review.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/dgouron/review-flow/review-followup-example
View source ↗ DGouron/review-flow dgouron.github.io
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.

Any agent
npx skills add DGouron/review-flow --skill review-followup-example
Clone the repo
git clone --depth 1 https://github.com/DGouron/review-flow

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 review-followup-example

README.md
[![agentmods](https://agentmods.dev/badge/skills/dgouron/review-flow/review-followup-example/github.svg)](https://agentmods.dev/skills/dgouron/review-flow/review-followup-example)
Your own site
<a href="https://agentmods.dev/skills/dgouron/review-flow/review-followup-example"><img src="https://agentmods.dev/badge/skills/dgouron/review-flow/review-followup-example/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 review-followup-example

Your own site · 80×15
<a href="https://agentmods.dev/skills/dgouron/review-flow/review-followup-example"><img src="https://agentmods.dev/badge/skills/dgouron/review-flow/review-followup-example.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 23 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 315 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. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
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 5.1 $0.00023 $0.00315
Opus 5.5 $0.00009 $0.00126
Sonnet 5.5 $0.00005 $0.00063
Haiku 4.5 $0.00002 $0.00032

Measured 2mo ago against content hash 20c2ea662d01, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

review-followup-example 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 2mo 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.

examples/skills/review-followup-example/SKILL.md · 54 lines

What it actually says

Review Follow-up Example

Context

You are: A reviewer verifying that previous review comments have been addressed.

Your goal: Confirm fixes are correct and detect any new issues introduced.

Workflow

  1. Read previous review from the MR comments
  2. Identify blocking issues that were raised
  3. Verify each fix in the new commits
  4. Check for regressions or new problems

Verification Checklist

For each blocking issue from the initial review:

  • Issue has been addressed
  • Fix is correct and complete
  • No new issues introduced by the fix

Output Format

Generate a concise follow-up report:

# Follow-up Review - MR #123

## Previous Blocking Issues Status

| Issue | Status | Notes |
|-------|--------|-------|
| Missing error handling in fetchUser() | ✅ Fixed | Added try/catch with proper error propagation |
| SQL injection in search query | ✅ Fixed | Now using parameterized queries |

## New Issues Detected
- None

## Verdict
✅ Ready to merge

Verdict Options

  • ✅ Ready to merge: All blocking issues fixed, no new problems
  • ⚠️ Needs minor fixes: Small issues found, another iteration needed
  • ❌ Major issues: Significant problems introduced, needs rework
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. 2mo ago First seen · 54 lines · 23 tokens per session scan A 20c2ea662d01

Subscribe to this mod's changes

review-followup-example is a skill published in the GitHub repository DGouron/review-flow (44 stars, last pushed 3d ago), licensed MIT. It adds 23 tokens to every session and 315 once invoked, about $0.0001 per session on Opus 5.5. 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.

Code reviewaiautomationclaudeclean-architecturedashboard
Related

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review-followup-example next to 6 skills from other repositories
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