Borrowing it
Nothing to install: this file belongs to llama-farm/llamafarm. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/llama-farm/llamafarm/main/.claude/skills/code-review/SKILL.mdgit clone --depth 1 https://github.com/llama-farm/llamafarmWrote 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.
[](https://agentmods.dev/skills/llama-farm/llamafarm/code-review)<a href="https://agentmods.dev/skills/llama-farm/llamafarm/code-review"><img src="https://agentmods.dev/badge/skills/llama-farm/llamafarm/code-review.svg" alt="Measured on agentmods" height="20"></a>- Socket pass
- Snyk fail
- NVIDIA SkillSpector pass
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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00041 | $0.02261 |
| Opus 5 | $0.00020 | $0.01130 |
| Sonnet 5 | $0.00008 | $0.00452 |
| Haiku 4.5 | $0.00004 | $0.00226 |
Grade A, and why
code-review scanned grade A with 1 finding 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.
Runs shell commandslowCapability
Expected in a hook, worth knowing in a rule or an instructions file.
- Python: `subprocess` with `shell=True`, `os.system(` How it starts
The opening of the file, as written. The whole thing — 354 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Code Review Skill
You are performing a comprehensive code review on a diff. Your task is to analyze the changed code for security vulnerabilities, anti-patterns, and quality issues.
Input Model
This skill expects a diff to be provided in context before invocation. The caller is responsible for generating the diff.
Example invocations:
- User pastes PR diff, then runs
/code-review - Agent runs
git diff HEAD~1, then invokes this skill - CI tool provides diff content for review
If no diff is present in context, ask the user to provide one or offer to generate one (e.g., git diff, git diff main..HEAD).
Domain Detection
Auto-detect which checklists to apply based on directory paths in the diff:
| Directory | Domain | Checklist |
|---|---|---|
designer/ |
Frontend | Read frontend.md |
server/ |
Backend | Read backend.md |
rag/ |
Backend | Read backend.md |
runtimes/universal/ |
Backend | Read backend.md |
cli/ |
CLI/Go | Generic checks only |
config/ |
Config | Generic checks only |
If the diff spans multiple domains, load all relevant checklists.
Review Process
Step 1: Parse the Diff
Extract from the diff:
- List of changed files
- Changed lines (additions and modifications)
- Detected domains based on file paths
Step 2: Initialize the Review Document
Create a review document using the temp-files pattern:
SANITIZED_PATH=$(echo "$PWD" | tr '/' '-')
REPORT_DIR="/tmp/claude/${SANITIZED_PATH}/reviews"
mkdir -p "$REPORT_DIR"
TIMESTAMP=$(date +%Y%m%d-%H%M%S)
FILEPATH="${REPORT_DIR}/code-review-${TIMESTAMP}.md"
Initialize with this schema:
# Code Review Report
**Date**: {current date}
**Reviewer**: Code Review Agent
**Source**: {e.g., "PR diff", "unstaged changes", "main..HEAD"}
**Files Changed**: {count}
**Domains Detected**: {list}
**Status**: In Progress
## Summary
| Category | Items Checked | Passed | Failed | Findings |
|----------|---------------|--------|--------|----------|
| Security | 0 | 0 | 0 | 0 |
| Code Quality | 0 | 0 | 0 | 0 |
| LLM Code Smells | 0 | 0 | 0 | 0 |
| Impact Analysis | 0 | 0 | 0 | 0 |
| Simplification | 0 | 0 | 0 | 0 |
{domain-specific categories added based on detected domains}
## Detailed Findings
{findings added here as review progresses}
What ships with it
2 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.
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.
- 8d ago First seen · 354 lines · 41 tokens per session scan A 8fec79e65c18
code-review is a skill published in the GitHub repository llama-farm/llamafarm (838 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 41 tokens to every session and 2,261 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 1 finding (runs shell commands). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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