code-review-assistant

Expert code reviewer focusing on quality, maintainability, performance, and best practices

8 stars

Best use case

code-review-assistant is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Expert code reviewer focusing on quality, maintainability, performance, and best practices

Teams using code-review-assistant should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/code-review-assistant/SKILL.md --create-dirs "https://raw.githubusercontent.com/sandraschi/advanced-memory-mcp/main/skills/technical/code-review-assistant/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/code-review-assistant/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How code-review-assistant Compares

Feature / Agentcode-review-assistantStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

Expert code reviewer focusing on quality, maintainability, performance, and best practices

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

Related Guides

SKILL.md Source

# Code Review Assistant
> **Status**: ✅ Research complete
> **Last validated**: 2025-11-08
> **Confidence**: 🟡 Medium — Research-backed guidance – review quarterly

## How to use this skill
1. Triage change context via [modules/core-guidance.md](modules/core-guidance.md).
2. Apply review heuristics from [modules/review-techniques.md](modules/review-techniques.md).
3. Leverage automation described in [modules/automation-and-tooling.md](modules/automation-and-tooling.md).
4. Align team rituals and metrics using [modules/team-practices.md](modules/team-practices.md).
5. Track open research follow-ups in [modules/known-gaps.md](modules/known-gaps.md) and refresh quarterly with [modules/research-checklist.md](modules/research-checklist.md).

## Module overview
- [Core guidance](modules/core-guidance.md) — sets review goals, scope, and triage questions.
- [Review techniques](modules/review-techniques.md) — checklist, heuristics, language-specific tips.
- [Automation & tooling](modules/automation-and-tooling.md) — bots, static analysis, AI assistance, metrics.
- [Team practices](modules/team-practices.md) — guidelines, onboarding, continuous improvement.
- [Known gaps](modules/known-gaps.md) — outstanding experiments and deeper dives.
- [Research checklist](modules/research-checklist.md) — quarterly validation workflow.

## Research status
- Verified against Google/Microsoft guidance and 2024 GitHub review metrics.
- Next update due 2026-02-01 or sooner if new GenAI-assisted review policies emerge.
- Known gaps capture future experiments (e.g., AI suggestions, pair review metrics).*** End Patch

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