classify-review-comment

classify-review-comment is a skill for Claude Code, Codex from wangke19/gemini-ai-helpers. It costs 87 tokens per session (2,809 once invoked), scanned A, a copy of classify-review-comment, Apache-2.0.

A tool for labeling GitHub pull-request review comments by severity and topic. GitHub pull requests are proposed code changes that can receive reviewer feedback.

In plain words
What is it for?
Use it to classify one comment, a comment link, or all comments in a pull request, following the supplied label definitions.
Why use it?
It turns unstructured review feedback into consistent categories, making recurring problems easier to track and understand.

Skill for Claude CodeCodex

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

Good fit Use it to classify one comment, a comment link, or all comments in a pull request, following the supplied label definitions.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/wangke19/gemini-ai-helpers/classify-review-comment
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 wangke19/gemini-ai-helpers --skill classify-review-comment
Clone the repo
git clone --depth 1 https://github.com/wangke19/gemini-ai-helpers

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 classify-review-comment

README.md
[![agentmods](https://agentmods.dev/badge/skills/wangke19/gemini-ai-helpers/classify-review-comment/github.svg)](https://agentmods.dev/skills/wangke19/gemini-ai-helpers/classify-review-comment)
Your own site
<a href="https://agentmods.dev/skills/wangke19/gemini-ai-helpers/classify-review-comment"><img src="https://agentmods.dev/badge/skills/wangke19/gemini-ai-helpers/classify-review-comment/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 classify-review-comment

Your own site · 80×15
<a href="https://agentmods.dev/skills/wangke19/gemini-ai-helpers/classify-review-comment"><img src="https://agentmods.dev/badge/skills/wangke19/gemini-ai-helpers/classify-review-comment.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 87 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,809 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 $0.00087 $0.02809
Opus 5 $0.00044 $0.01404
Sonnet 5 $0.00017 $0.00562
Haiku 4.5 $0.00009 $0.00281

Measured 10d ago against content hash 2cfd1293cdc7, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

classify-review-comment 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.

Origin

This is a copy

100% identical to classify-review-comment — 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.

extensions/code-review/skills/classify-review-comment/SKILL.md · 228 lines

How it starts

The opening of the file, as written. The whole thing — 228 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Classify Review Comments

Classify GitHub pull request review comments into severity and topic categories. Works with a single comment (text), a GitHub comment URL, or an entire PR (classifies all comments).

This enables tracking review feedback patterns: what kinds of issues reviewers catch, how severe they are, and where AI-generated code needs the most improvement.

Labels

Read the labels file before classifying any comments:

config.json (in the same directory as this skill)

The labels file defines the exact set of valid values for severity and topic. You MUST select from these values — do not invent new labels. Each label includes a description and signal words or examples to guide your selection.

Classification rule: For each comment, find the single best-matching severity and single best-matching topic from the labels file. Match based on the label's description, signals/examples, and the comment content. Use unclassified only when no other label fits.

Input Modes

1. Single Comment (text)

Classify a comment provided directly as text.

Input: The raw comment body. Output: A single classification object.

2. Comment URL

Fetch a specific comment by its GitHub URL and classify it.

URL formats supported:

  • https://github.com/{owner}/{repo}/pull/{number}#issuecomment-{id}
  • https://github.com/{owner}/{repo}/pull/{number}#discussion_r{id}
  • https://github.com/{owner}/{repo}/pull/{number}#pullrequestreview-{id}

Fetch with:

# Issue comment
gh api repos/{owner}/{repo}/issues/comments/{id} --jq '{author: .user.login, body: .body}'

# Review comment (discussion)
gh api repos/{owner}/{repo}/pulls/comments/{id} --jq '{author: .user.login, body: .body}'

# Review body comment
gh api repos/{owner}/{repo}/pulls/{number}/reviews/{id} --jq '{author: .user.login, body: .body}'

3. Full PR

Fetch all comments on a PR, filter out noise, and classify each one.

URL format: https://github.com/{owner}/{repo}/pull/{number}

Read the full file on GitHub · 228 lines

Files

What ships with it

1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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. 10d ago First seen · 228 lines · 87 tokens per session scan A 2cfd1293cdc7

Subscribe to this mod's changes

classify-review-comment is a skill published in the GitHub repository wangke19/gemini-ai-helpers (2 stars, last pushed 5mo ago), licensed Apache-2.0. It adds 87 tokens to every session and 2,809 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to classify-review-comment, differing in 0 lines, and is treated as a copy.

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