CO

coderabbit-local-dev-loop

Automates local AI-powered code reviews using the CodeRabbit CLI to catch issues before committing.

Install

mkdir -p .claude/skills/coderabbit-local-dev-loop && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/4758" && unzip -o skill.zip -d .claude/skills/coderabbit-local-dev-loop && rm skill.zip

Installs to .claude/skills/coderabbit-local-dev-loop

Activation

This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.

Configure CodeRabbit CLI for local pre-commit code reviews and fast
67 charsno explicit “when” trigger
Intermediate

Key capabilities

  • Perform local AI code reviews
  • Integrate reviews into git hooks
  • Review specific files or staged changes
  • Provide interactive feedback via terminal
  • Configure review path instructions

How it works

The CLI runs AI-powered reviews against local git changes, allowing developers to receive feedback before pushing code. It supports integration into git hooks and VS Code tasks for automated workflows.

Inputs & outputs

You give it
Staged git changes or specific file paths
You get back
AI-generated code review feedback in terminal

When to use coderabbit-local-dev-loop

  • Perform pre-commit reviews on local changes
  • Test CodeRabbit configuration changes
  • Review specific files before pushing
  • Streamline git commit workflows with AI checks

About this skill

CodeRabbit Local Dev Loop

Overview

Use CodeRabbit CLI to review code locally before opening a PR. The CLI provides the same AI-powered review as the GitHub App but runs in your terminal against staged or unstaged changes. This creates a multi-layered review process: local CLI review before commit, then automated PR review after push.

Prerequisites

  • CodeRabbit CLI installed (curl -fsSL https://cli.coderabbit.ai/install.sh | sh)
  • Git repository with .coderabbit.yaml configuration
  • CodeRabbit account (CLI uses credits: $0.25 per file reviewed)

Instructions

Step 1: Install and Verify CLI

set -euo pipefail
# Install CodeRabbit CLI
curl -fsSL https://cli.coderabbit.ai/install.sh | sh

# Verify installation
cr --version

# Authenticate (opens browser for OAuth)
cr auth login

Step 2: Local Review Workflow

set -euo pipefail
# Review all staged changes (most common workflow)
git add -A
cr review

# Review specific files only
cr review src/api/routes.ts src/middleware/auth.ts

# Interactive mode: ask follow-up questions about review feedback
cr review --interactive

# Plain output mode (pipe to other tools or AI agents)
cr review --prompt-only

Step 3: Git Hook Integration

#!/bin/bash
# .git/hooks/pre-push (make executable: chmod +x .git/hooks/pre-push)
set -euo pipefail

echo "Running CodeRabbit pre-push review..."

# Get list of changed files vs remote
CHANGED_FILES=$(git diff --name-only @{push}.. 2>/dev/null || git diff --name-only HEAD~1)

if [ -n "$CHANGED_FILES" ]; then
  echo "$CHANGED_FILES" | xargs cr review

  # Non-blocking: show review but don't prevent push
  # To make blocking, check exit code:
  # echo "$CHANGED_FILES" | xargs cr review || {
  #   echo "CodeRabbit found issues. Push anyway? (y/n)"
  #   read -r response
  #   [ "$response" != "y" ] && exit 1
  # }
fi

Step 4: Configuration for Local Development

# .coderabbit.yaml - Settings that affect both CLI and PR reviews
language: "en-US"
reviews:
  profile: "assertive"
  path_instructions:
    - path: "src/**"
      instructions: "Check for proper error handling and type safety."
    - path: "tests/**"
      instructions: "Verify edge cases and assertion completeness."
  path_filters:
    - "!**/*.lock"
    - "!dist/**"
    - "!**/*.generated.*"
  auto_review:
    enabled: true
    drafts: false
chat:
  auto_reply: true

Step 5: IDE Integration Pattern

// .vscode/tasks.json - Run CodeRabbit review from VS Code
{
  "version": "2.0.0",
  "tasks": [
    {
      "label": "CodeRabbit: Review Current File",
      "type": "shell",
      "command": "cr review ${file}",
      "presentation": { "reveal": "always", "panel": "shared" },
      "problemMatcher": []
    },
    {
      "label": "CodeRabbit: Review Staged Changes",
      "type": "shell",
      "command": "cr review",
      "presentation": { "reveal": "always", "panel": "shared" },
      "problemMatcher": []
    }
  ]
}

Two-Layer Review Strategy

Developer writes code
       │
       ▼
┌──────────────────┐
│ cr review (local) │  ← Layer 1: Fast feedback before commit
│ Fix obvious issues│
└────────┬─────────┘
         │
         ▼
   git commit + push
         │
         ▼
┌──────────────────┐
│ CodeRabbit App   │  ← Layer 2: Full context review on PR
│ (automated PR    │
│  review)         │
└──────────────────┘

Output

  • CodeRabbit CLI installed and authenticated
  • Pre-push git hook for automated local reviews
  • VS Code task integration for on-demand reviews
  • Two-layer review workflow (local + PR)

Error Handling

IssueCauseSolution
cr: command not foundCLI not in PATHRe-run install script or add to PATH
Auth token expiredSession timeoutRun cr auth login again
"No credits remaining"Usage-based billing exhaustedPurchase credits at app.coderabbit.ai
Review hangs on large fileFile too large for AI contextReview specific files instead of all
Empty review outputNo changed files detectedStage changes with git add first

Resources

Next Steps

See coderabbit-sdk-patterns for PR interaction automation patterns.

When not to use it

  • Reviewing files without git staging
  • Replacing full PR-based automated reviews

Prerequisites

CodeRabbit CLI installedGit repository with .coderabbit.yaml configurationCodeRabbit account

Limitations

  • Requires internet access for AI review processing
  • Usage-based billing applies per file reviewed

How it compares

This approach provides immediate AI feedback locally before a commit, whereas standard PR reviews only occur after code is pushed to the remote repository.

Compared to similar skills

coderabbit-local-dev-loop side by side with the closest alternatives in the catalog.

SkillInstallsUpdatedSafetyDifficulty
coderabbit-local-dev-loop (this skill)127dReviewIntermediate
subagent-driven-development147moNo flagsAdvanced
swarm-coordination06moNo flagsAdvanced
resolve-conflicts818moReviewIntermediate

Try saying

Example prompts that trigger this skill in your AI assistant.

More by jeremylongshore

View all by jeremylongshore

analyzing-logs

jeremylongshore

Analyze application logs to detect performance issues, identify error patterns, and improve stability by extracting key insights.

14123

ollama-setup

jeremylongshore

Configure auto-configure Ollama when user needs local LLM deployment, free AI alternatives, or wants to eliminate hosted API costs. Trigger phrases: "install ollama", "local AI", "free LLM", "self-hosted AI", "replace OpenAI", "no API costs". Use when appropriate context detected. Trigger with relevant phrases based on skill purpose.

1167

backtesting-trading-strategies

jeremylongshore

Backtest crypto and traditional trading strategies against historical data. Calculates performance metrics (Sharpe, Sortino, max drawdown), generates equity curves, and optimizes strategy parameters. Use when user wants to test a trading strategy, validate signals, or compare approaches. Trigger with phrases like "backtest strategy", "test trading strategy", "historical performance", "simulate trades", "optimize parameters", or "validate signals".

1071

generating-database-seed-data

jeremylongshore

Process this skill enables AI assistant to generate realistic test data and database seed scripts for development and testing environments. it uses faker libraries to create realistic data, maintains relational integrity, and allows configurable data volumes. u... Use when working with databases or data models. Trigger with phrases like 'database', 'query', or 'schema'.

1033

cursor-codebase-indexing

jeremylongshore

Execute set up and optimize Cursor codebase indexing. Triggers on "cursor index setup", "codebase indexing", "index codebase", "cursor semantic search". Use when working with cursor codebase indexing functionality. Trigger with phrases like "cursor codebase indexing", "cursor indexing", "cursor".

885

testing-mobile-apps

jeremylongshore

Execute mobile app testing on iOS and Android devices/simulators. Use when performing specialized testing. Trigger with phrases like "test mobile app", "run iOS tests", or "validate Android functionality".

810

You might also like

subagent-driven-development

davila7

Use when executing implementation plans with independent tasks in the current session

1493

swarm-coordination

joelhooks

Multi-agent coordination patterns for OpenCode swarm workflows. Use when work benefits from parallelization or coordination.

04

resolve-conflicts

antinomyhq

Use this skill immediately when the user mentions merge conflicts that need to be resolved. Do not attempt to resolve conflicts directly - invoke this skill first. This skill specializes in providing a structured framework for merging imports, tests, lock files (regeneration), configuration files, and handling deleted-but-modified files with backup and analysis.

81334

claude-automation-recommender

anthropics

Analyze a codebase and recommend Claude Code automations (hooks, subagents, skills, plugins, MCP servers). Use when user asks for automation recommendations, wants to optimize their Claude Code setup, mentions improving Claude Code workflows, asks how to first set up Claude Code for a project, or wants to know what Claude Code features they should use.

47140

codex-skill

feiskyer

Use when user asks to leverage codex, gpt-5, or gpt-5.1 to implement something (usually implement a plan or feature designed by Claude). Provides non-interactive automation mode for hands-off task execution without approval prompts.

12110

agent-factory

alirezarezvani

Claude Code agent generation system that creates custom agents and sub-agents with enhanced YAML frontmatter, tool access patterns, and MCP integration support following proven production patterns

8109

Search skills

Search the agent skills registry