Agent skill · Code Review & Quality

ralph-review-trio

Run a sequential three-tier code review on a finished implementation branch — Haiku (surface) → Sonnet (logic) → Opus (deep). Restarts from Tier 1 on any tier failure. Use when a solo branch or PR is code-complete and you want structured pre-merge verification before human review.

davepoongithub.com/davepoonGitHub ↗
claude-codeMIT
Install
npx skills add davepoon/buildwithclaude --skill ralph-review-trio --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 6
SKILL.md size: 2 KB
Bundled scripts: none
Path: plugins/ralph-review-trio/skills/ralph-review-trio/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 3,251
Language: TypeScript
Read our review of the source →

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# Ralph Review Trio This skill triggers `/ralph-review`, which runs three sequential reviewer subagents at increasing depth. If any tier flags a failure, the loop restarts from Tier 1 after fixes. ## When to trigger - An implementation is code-complete on a feature / solo branch. - All acceptance criteria for the underlying issue are believed satisfied. - Pre-merge verification is needed before hu

More from buildwithclaude
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About this skill
What does the ralph-review-trio skill do?

Run a sequential three-tier code review on a finished implementation branch — Haiku (surface) → Sonnet (logic) → Opus (deep). Restarts from Tier 1 on any tier failure. Use when a solo branch or PR is code-complete and you want structured pre-merge verification before human review.

How do I install it?

Run `npx skills add davepoon/buildwithclaude --skill ralph-review-trio --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From davepoon/buildwithclaude, a repository with 3,251 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

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