code-reviewer
Use this skill when the user asks for a code review, wants to check code quality, find bugs, identify security issues, or get best practice suggestions.
Skill by techgangboss
Chalk Labs
Need help deploying code-reviewer?
Chalk Labs sets up agents like this inside real teams: connected to your tools, tested on your data, with a human in the loop where it matters.
Install
Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.
npx agentmarket install skill/techgangboss-code-reviewer
Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.
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About
Use cases: security
Reviews
Write a reviewNo reviews yet. Installed it? Reviews come from verified installers only. How reviews work
Permissions
What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.
- Tools
- No tools found
- Secrets
- None asked for
- Install scripts
- None found
Network hosts it talks to 1
codeload.github.com· found in install command
Files it touches
~/.claude/skills/code-reviewer
What's inside
- Skill name
code-reviewer- Description
- Use this skill when the user asks for a code review, wants to check code quality, find bugs, identify security issues, or get best practice suggestions. Trigger on phrases like "review this code", "check for bugs", "security audit", "code quality", "review my PR", "what's wrong with this code", etc.
- License
- MIT
- Instructions
- 84 lines in SKILL.md · view on GitHub
Agent Skills spec issues
- name: missing
Files (1)
- SKILL.md
SKILL.md (first lines)
# Code Reviewer AI-powered code review that analyzes code for bugs, security vulnerabilities, performance issues, and adherence to best practices. ## Capabilities - Bug detection and logical error analysis - Security vulnerability scanning (OWASP Top 10) - Performance issue identification - Best practice and style suggestions - Dependency risk assessment ## Instructions When the user asks for a code review: ### 1. Gather Context - Identify the files to review (user may specify, or review staged/changed files via `git diff`) - Determine the language and framework - Check for project conventions (linting config, `.editorconfig`, etc.) ### 2. Analyze for Issues Review each file systematically for: **Bugs & Logic Errors:** - Off-by-one errors, null/undefined access, race conditions - Incorrect type handling, missing error cases - Logic that doesn't match stated intent **Security (OWASP Top 10):** - SQL injection, XSS, command injection - Hardcoded secrets or credentials - Insecure deserialization, SSRF - Missing input validation at system boundaries - Improper authentication/authorization checks **Performance:** - N+1 queries, unnecessary re-renders - Missing indexes for database queries - Unbounded loops or memory leaks - Synchronous operations that should be async **Best Practices:** - Dead code, unused variables/imports - Missing error handling at API boundaries - Inconsistent naming conventions - Functions doing too many things ### 3. Report Findings Format the review as: ``` ## Code Review Summary ### Critical Issues (must fix) - [FILE:LINE] Description of critical bug or security issue ### Warnings (should fix) - [FILE:LINE] Description of potential problem ### Suggestions (nice to have) - [FILE:LINE] Style or best practice improvement ### What Looks Good - Positive observations about well-written code ``` ### 4. Offer Fixes For each critical issue and warning, offer to generate a fix. Use the Edit tool to apply fixes the user approves. ## Example **User:** "Review the changes in my last commit" 1. Run `git diff HEAD~1` to see changes 2. Analyze each changed file 3. Report findings grouped by severity 4. Offer to fix critical issues
From techgangboss/agentstore, MIT.
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Signals
- Stars
- 5
- Forks
- 0
- Open issues
- 1
- Last commit (this folder)
- Feb 8, 2026 (8 months ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- MIT
- Repository
- github.com/techgangboss/agentstore
- Website
- agentstore.tools
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
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Done for you
Rather not set it up yourself?
Chalk Labs scopes, builds and runs agents for your team: the task audit, the eval harness, the integrations and the weekly ops report. Fixed scope, priced before we start.
See how we build AI agents →Read the case studies
Chalk Labs is a two-founder AI and growth studio. We build AI agents, CRMs and MVPs for Web3 and AI companies, and have shipped 50+ product and token launches.
- launches shipped
- 50+
- launches shipped
- media placements
- 500+
- media placements
- founders on every account
- 2
- founders on every account
Press we've placed: Forbes · CoinDesk · Decrypt · Cointelegraph · The Block
Rahil Jain, Co-founder, Chalk Labs. Ex-Goldman Sachs engineer. You talk to the person who builds it.
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Cite this page
code-reviewer skill. Agent Mart. https://agentmart.dev/skills/techgangboss-code-reviewer (last updated 2026-10-24)