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 Review Loop

Overview

Use the native CLI before push and feed findings back into coding. Keep auth, scope, and spend visible.

Prerequisites

  • Identify the CodeRabbit organization, Git provider, repository, plan, and accountable owner.
  • Read references/official-docs.md and re-check any time-sensitive contract before execution.
  • Use synthetic or read-only evidence until the approval boundary is satisfied.
  • Preserve the repository's independent CI, security, and human-review requirements.

Current Contract

  • The CLI reviews local changes before commit.
  • coderabbit review --plain is the agent-friendly command.
  • Interactive and Agentic-key login are distinct.
  • CLI allowances and billing follow current plan contracts.

Authentication

Treat Git-provider sessions, CodeRabbit web sessions, CLI credentials, and CodeRabbit API keys as separate credentials. Use only an already-approved session or secret-manager reference, never print a secret, and do not place credentials in .coderabbit.yaml, source files, logs, or deliverables.

Instructions

  1. Confirm repo state, diff scope, auth mode, allowance, and excluded files.

  2. Run a bounded plain review and capture findings without secrets.

  3. Classify findings, fix approved items, and rerun changed scope.

  4. Stop on repeats, scope expansion, auth errors, or usage limits.

Tool Discipline

  • Use Glob to locate candidate configuration and evidence files without widening scope.
  • Use Grep to find relevant fields, commands, identifiers, and stale claims.
  • Use Read to inspect the smallest required files and authoritative evidence.
  • Use Write only for a new approved local draft or evidence artifact.
  • Use Edit only for a bounded approved change whose rollback is known.
  • Do not use these file tools as a substitute for authenticated CodeRabbit or provider operations.

Approval Boundaries

Require approval before credits, headless keys, wider review scope, or pushing. Keep analysis and drafts local until approval is explicit, and record who approved the action and its scope.

Output

A receipt with scope, mode, dispositions, changed files, rerun result, and risks. Include source dates, unknowns, and the exact boundary between observed fact and recommendation.

Error Handling

ConditionResponse
Current contract is unclear or docs disagreeStop mutation, cite both sources, and request owner resolution.
Required access or approval is missingProduce a draft and evidence plan only.
Validation or pilot behavior differs from expectationRestore the prior state and retain the failed evidence.
Output contains secrets or private codeStop, quarantine the artifact, redact it, and notify the data owner.

Examples

Example 1

Review staged changes before commit and rerun after a race fix.

Example 2

Use Codex integration with injected secret auth.

Validation

  • Confirm every claim against the dated sources in references/official-docs.md.
  • Verify the requested scope, owner, approval, happy path, failure path, and rollback.
  • Re-read the effective configuration or provider state after any approved change.
  • Report unsupported fields, undocumented endpoints, and unverified assumptions as failures.

Resources

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)12moReviewIntermediate
subagent-driven-development149moNo flagsAdvanced
swarm-coordination07moNo flagsAdvanced
resolve-conflicts8110moReviewIntermediate

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