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code-review

Use when a feature branch needs adversarial review before PR: the configured reviewer, resolve findings, re-run lint and tests, loop to LGTM.

Skill by arbor-ai-inc

IndexedApache-2.0
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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/arbor-ai-inc-code-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.

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About

Use when a feature branch needs adversarial review before PR: the configured reviewer, resolve findings, re-run lint and tests, loop to LGTM.

Use cases: agent-building

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What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.

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Network hosts it talks to 1

  • codeload.github.com · found in install command

Files it touches

  • ~/.claude/skills/code-review

What's inside

Skill name
code-review
Description
Use when a feature branch needs adversarial review before PR: the configured reviewer, resolve findings, re-run lint and tests, loop to LGTM.
License
Apache-2.0
Instructions
20 lines in SKILL.md · view on GitHub

Files (1)

  • SKILL.md

SKILL.md (first lines)

<!-- GENERATED by scripts/gen_adapters.py from skills/code-review/SKILL.md.
Do not edit: run the generator instead. The canonical workflow is
reference/code-review.md; this file only routes an agent to it. -->
**In Claude Code, check the model first, and again on every resume after a stop** (Codex: skip). Read `model_pins["code-review"]` from `python3 .cadence/tools/cadence_config.py --json`; if it is set and you are not running on it, say so and stop — name both models and how to switch (`/model <name>`). Continue only if the author says to. Unset: no check.

Reviewer is `[review].provider`: `codex` (`codex exec`), `claude` (`claude -p`), `subagent` (Claude Code only — needs Task), `coderabbit`, or `none`. **Pick a different agent from the one that wrote the code**; that is the whole point.

Follow the canonical procedure in `.cadence/reference/code-review.md` exactly.

Never the context that wrote the code. Give the reviewer the architectural context, not just the diff: principles subset, boundary docs, contract files. Trace written payloads to their consumer.

Lint + tests green before round 1 and after every resolution round.

Resolve all BLOCKER/SHOULD findings; product questions go to the ask transport via `.cadence/tools/ask.py`.

Circuit breaker at `[review].circuit_breaker` rounds (default 3): post open findings on the issue and to the ask transport, and stop. Never merge.

On LGTM, hand back a Shape B change brief per `.cadence/reference/human-brief.md` — plain-English consequences, evidence per row, and where the reviewer and I disagreed.

From arbor-ai-inc/cadence, Apache-2.0.

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Last commit (this folder)
Oct 9, 2026 (19 days ago)

From GitHub (fetched Oct 24, 2026).

Details

License
Apache-2.0
First seen
Oct 24, 2026
Last checked
Oct 24, 2026

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Cite this page

code-review skill. Agent Mart. https://agentmart.dev/skills/arbor-ai-inc-code-review (last updated 2026-10-24)