github-review

A workflow for handling review comments on GitHub pull requests, which are proposed code changes awaiting review.

In plain words
What is it for?
Use it to retrieve comments, inspect the relevant code, choose an approach, and carry out fixes across one or more pull requests.
Why use it?
It helps turn scattered review feedback into a planned set of fixes while keeping the repository's branching workflow consistent.

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/wrannaman/agentic-engineering/github-review
Any agent
npx skills add wrannaman/agentic-engineering --skill github-review
Clone the repo
git clone --depth 1 https://github.com/wrannaman/agentic-engineering

Made for: Claude Code, Codex.

Per session 20 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,704 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 $0.00020 $0.02704
Opus 5 $0.00010 $0.01352
Sonnet 5 $0.00004 $0.00541
Haiku 4.5 $0.00002 $0.00270

Measured 2d ago against content hash a6e3549e522a, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

github-review 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.

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.

skills/quality/github-review/SKILL.md · 392 lines

How it starts

The opening of the file, as written. The whole thing — 392 lines — stays where its author put it; the contents beside it link to each section on GitHub.

GitHub Review Skill

You are entering the github-review phase. You will address review comments from a GitHub Pull Request.

Process

Step 0: Detect Stack Structure

Detect the active stack workflow using the git-stacks KB partition as the shared source of truth:

  1. list_kb_documents for partition git-stacks

  2. read_kb_document_by_path for /index.md

  3. Run the dedicated-client checks from git-stacks/index.md

    • If a dedicated client is detected, record STACK_CLIENT accordingly
    • If no dedicated client is detected, inspect the current PR base and local branch relationships to decide whether this repo is using a native git stack
    • If confirmed, record STACK_CLIENT=native-git
  4. Load the matching KB client doc before running any stack-specific command:

    • charcoalread_kb_document_by_path for /charcoal.md
    • git-townread_kb_document_by_path for /git-town.md
    • native-gitread_kb_document_by_path for /native-git.md
    • Use the client doc as the source of truth for stack navigation commands

If in a stack:

  • You may have multiple PRs with review comments
  • Present option to address comments from all PRs or just current

Present to user (if in stack):

## Stack Detected

Your stack has N PRs with open review comments:
| PR | Branch | Open Comments |
|----|--------|---------------|
| #123 | feat/part-1 | 2 |
| #124 | feat/part-2 | 5 |
| #125 | feat/part-3 | 0 |

How would you like to proceed?
1. Address all PRs (recommended) - Fix comments across all PRs
2. Address current PR only (#124) - Fix comments on feat/part-2 only

Step 1: Pull OPEN (Unresolved) PR Review Comments

For stacked PRs: Pull comments from each PR in scope.

First, identify the PR(s) and pull only unresolved review threads using GraphQL (the REST API does not expose resolved/unresolved status):

# Get PR number and basic info from current branch
gh pr view --json number,title,url,reviewDecision

# Get ONLY unresolved review threads using GraphQL
gh api graphql -f query='
query($owner: String!, $repo: String!, $pr: Int!) {
  repository(owner: $owner, name: $repo) {
    pullRequest(number: $pr) {
      reviewThreads(first: 100) {
        nodes {
          isResolved
          path
          line
          comments(first: 10) {
            nodes {
              author { login }
              body
              createdAt
            }
          }
        }
      }
    }
  }
}' -f owner='{owner}' -f repo='{repo}' -F pr=<PR_NUMBER>

Read the full file on GitHub · 392 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. 2d ago First seen · 392 lines · 20 tokens per session scan A a6e3549e522a

Subscribe to this mod's changes

github-review is a skill published in the GitHub repository wrannaman/agentic-engineering (2 stars, last pushed 4mo ago), licensed MIT. It adds 20 tokens to every session and 2,704 once invoked, about $0.0001 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 2026-08-31.

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