code-reviewer

code-reviewer is a skill for Claude Code from XRenSiu/claude-code-forge. It costs 270 tokens per session (4,188 once invoked), scanned A, original, MIT.

A code-diff reviewer that looks for bugs in changed code. It can focus on security, logic, performance, style, or all of these.

In plain words
What is it for?
Use it to inspect a pull request, branch, directory, or code snippet and receive a structured list of evidence-based findings.
Why use it?
It helps find defects without mixing code review with requirement checks or test execution.

Skill for Claude Code

Written for Claude Code: user-invocable in frontmatter. Also seen: mentions CLAUDE.md; mentions subagents; mentions Codex.

Part of the ai-dlc plugin — 30 skills, 5 agents shipped together

Good fit Use it to inspect a pull request, branch, directory, or code snippet and receive a structured list of evidence-based findings.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/xrensiu/claude-code-forge/code-reviewer
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 XRenSiu/claude-code-forge --skill code-reviewer
Clone the repo
git clone --depth 1 https://github.com/XRenSiu/claude-code-forge

Made for: Claude Code.

Or install ai-dlc, the plugin that ships this one along with the rest of its 30 skills, 5 agents.

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 code-reviewer

README.md
[![agentmods](https://agentmods.dev/badge/skills/xrensiu/claude-code-forge/code-reviewer/github.svg)](https://agentmods.dev/skills/xrensiu/claude-code-forge/code-reviewer)
Your own site
<a href="https://agentmods.dev/skills/xrensiu/claude-code-forge/code-reviewer"><img src="https://agentmods.dev/badge/skills/xrensiu/claude-code-forge/code-reviewer/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 code-reviewer

Your own site · 80×15
<a href="https://agentmods.dev/skills/xrensiu/claude-code-forge/code-reviewer"><img src="https://agentmods.dev/badge/skills/xrensiu/claude-code-forge/code-reviewer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 270 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 4,188 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 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 $0.00270 $0.04188
Opus 5.5 $0.00108 $0.01675
Sonnet 5.5 $0.00054 $0.00838
Haiku 4.5 $0.00027 $0.00419

Measured 1mo ago against content hash 90beace28f44, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

code-reviewer 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 1mo 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.

plugins/ai-dlc/skills/code-reviewer/SKILL.md · 260 lines

How it starts

The opening of the file, as written. The whole thing — 260 lines — stays where its author put it; the contents beside it link to each section on GitHub.

code-reviewer — diff in, findings out

You are invoked to review a code diff (or branch, or directory) and emit a structured findings list. You do not check requirement compliance (that is /pm-reviewer), run tests (that is /qa-reviewer), or detect contract gaming (that is /spec-gaming-detector). You only look at the code itself for bugs.

Say once at the start, then start working:

"I'm using the code-reviewer skill, focus={focus}. Detective Loop: I'll read the diff, hop into related code as needed, emit up to 5 findings with evidence. No padding nits."

Do not narrate further — just walk the phases.


Iron rules (re-read before every run)

  1. One focus per session. When invoked with --focus=security, only flag security findings. Logic/perf/style/other categories are out of scope for this run — the user spawns a separate session for those (or --focus=all for a single Opus catch-all pass at higher token cost). Mixing focuses dilutes the signal; per Anthropic CR's fleet-by-focus pattern, narrow beats wide.
  2. Detective Loop, not flowchart. Do not impose a fixed read order. Read the diff first; then decide what to grep / read next based on what you see. Greptile v3 data: switching from flowchart to loop yielded +256% upvote/downvote ratio and +70.5% action rate. If the diff calls a function you don't see, read it; do not flag "cannot evaluate without context" — that is the agent failing, not the diff.
  3. Reproduction required for P0/P1. Every P0 or P1 finding must include a concrete reproduction_scenario field — a specific input, sequence, or state that triggers the bug. "Could be a problem under load" without a concrete trigger = downgrade to P2 or drop. Anthropic data: forcing reproduction crashed false positive rate from double-digit % to <1%.
  4. Asymmetric SNR — different rules for P0/P1 vs P2/P3. P0/P1 favor recall: flag anything that plausibly causes an incident, even with medium confidence. P2/P3 favor precision: only flag if you would stake the report on it. The middle confidence band on P2/P3 gets dropped, not reported as confidence: low — readers skim past low-confidence P2s and the signal-to-noise tanks.
  5. Hard cap: 5 findings per run. If you have more than 5 candidates, keep the top 5 by severity then evidence strength. The remaining issues are still there for the next reviewer / next iteration — your job is not to be exhaustive, it is to be useful. Anthropic's empirical finding: capped lists hit P0/P1 better than uncapped ones because the model self-prioritizes instead of padding.
  6. No findings ≠ no output. If you find nothing after honest effort, emit findings: [] with a one-line rationale: describing what code paths you walked. Do NOT pad with nits. Do NOT apologize. An empty findings list with a real rationale is high-signal: "I looked at X, Y, Z and the impl is clean within {focus}."
  7. Diff truncation awareness. You see the diff, not the whole repo. If the diff references something that may be defined elsewhere (import { foo } from '../bar'), do not flag "missing definition" — LOCATE + READ to verify. If you cannot verify within reasonable tool budget, mark the finding needs_codebase_check: true and let meta-judge / the user decide; do not invent a finding from absence of evidence.
  8. No sycophancy hedges. Forbidden phrases: "the code is generally well-structured", "this looks mostly correct", "might be worth considering", "as a minor suggestion". Either you have a finding with evidence or you do not. SycEval (2025): citation-based rebuttal is the most dangerous failure mode — once you start hedging, you cannot stop.
  9. Cross-vendor mode is structural, not optional, for adversarial intent. If the user wants an adversarial review (the default-reversed "assume this caused a prod incident, find why" prompt), prefer a non-Claude evaluator. If the runtime has Codex CLI or Gemini CLI, use it; if not, use a different Claude size (Haiku for terse hunt, Opus for deep) and log the same-vendor caveat. The default-reversal prompt fights some RLHF bias but cross-vendor fights it structurally.

Read the full file on GitHub · 260 lines

Files

What ships with it

5 files 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. 1mo ago Changed · +21 lines 90beace28f44
  2. 2mo ago First seen · 239 lines · 270 tokens per session scan A 399c8cc7957d

Subscribe to this mod's changes

code-reviewer is a skill published in the GitHub repository XRenSiu/claude-code-forge (2 stars, last pushed 1mo ago), licensed MIT. It adds 270 tokens to every session and 4,188 once invoked, about $0.0011 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 2026-08-31.

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