review
Review changes for correctness, risk, maintainability, and policy compliance.
Skill by donghyuck
Chalk Labs
Need help deploying review?
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/donghyuck-review
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.
Get the weekly diff
The weekly diff: one email a week with new agent tools, notable updates and grade changes, plus security alerts for tools you follow. Double opt-in, one-click unsubscribe.
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/review
What's inside
- Skill name
review- Description
- Review changes for correctness, risk, maintainability, and policy compliance.
- License
- MIT
- Instructions
- 12 lines in SKILL.md · view on GitHub
Files (1)
- SKILL.md
SKILL.md (first lines)
# Review Use before merge. - Review correctness, risk, maintainability, and policy compliance. - Check that the implementation matches the spec and acceptance criteria. - Look for regressions, missing validation, and unrelated changes. - Flag security, privacy, permission, or data-handling risks. - Give evidence-based findings with file paths, commands, or observed behavior. - Avoid vague comments that cannot be acted on.
From donghyuck/studio-api, MIT.
More from donghyuck/studio-api
- 0.542score
devops-policy-template-maintainer
donghyuck
Maintain this reusable AI-assisted DevOps policy template.
SkillBFreshness: B★ 1Claude Code +9 - 0.541score
write-commit
donghyuck
Prepare AI-assisted commit messages using the repository commit template and validation record.
SkillBFreshness: B★ 1Claude Code +9 - 0.541score
write-issue
donghyuck
Draft GitLab issues with the repository issue template and AI-assisted tracking fields.
SkillBFreshness: B★ 1Claude Code +9 - 0.541score
write-mr
donghyuck
Draft GitLab merge requests with Why, What, Validation, risk, and AI/subagent usage records.
SkillBFreshness: B★ 1Claude Code +9 - 0.536score
spec
donghyuck
Define task scope, constraints, acceptance criteria, and ambiguity before implementation.
SkillBFreshness: B★ 1Claude Code +9
Signals
- Stars
- 1
- Forks
- 0
- Open issues
- 13
- Last commit (this folder)
- Apr 20, 2026 (6 months ago)
- Last release
- Jul 26, 2026 (3 months ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- MIT
- Repository
- github.com/donghyuck/studio-api
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
More from donghyuck
- 0.542score
devops-policy-template-maintainer
donghyuck
Maintain this reusable AI-assisted DevOps policy template.
SkillBFreshness: B★ 1Claude Code +9 - 0.541score
write-commit
donghyuck
Prepare AI-assisted commit messages using the repository commit template and validation record.
SkillBFreshness: B★ 1Claude Code +9 - 0.541score
write-issue
donghyuck
Draft GitLab issues with the repository issue template and AI-assisted tracking fields.
SkillBFreshness: B★ 1Claude Code +9 - 0.541score
write-mr
donghyuck
Draft GitLab merge requests with Why, What, Validation, risk, and AI/subagent usage records.
SkillBFreshness: B★ 1Claude Code +9 - 0.536score
spec
donghyuck
Define task scope, constraints, acceptance criteria, and ambiguity before implementation.
SkillBFreshness: B★ 1Claude Code +9
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.
Get review running in your business
Tell us what you want to automate. A founder replies within one working day with a plan, not a pitch deck.
Cite this page
review skill. Agent Mart. https://agentmart.dev/skills/donghyuck-review (last updated 2026-10-24)