beagle

🥈Silver

Beagle is a Claude Code plugin for code review and verification workflows. It supports Python, Go, React, FastAPI, BubbleTea, and AI frameworks like Pydantic AI, LangGraph, and Vercel AI SDK. It helps developers automate code reviews and ensure code quality.

4820Updated 2mo ago

Intermediate30min to implementautomation

Saves ~60 min per use

Quick InstallView Source

git clone https://github.com/existential-birds/beagle.git

Works with:

Claude

Overview

About This Skill

Beagle is a Claude Code plugin marketplace containing 131 skills organized across code review, documentation, testing, architectural analysis, and git workflows. It supports multiple languages and frameworks including Python, Go, Rust, Elixir, React, Remix v2, iOS/Swift, and AI frameworks like Pydantic AI and LangGraph. Developers use Beagle to automate code reviews before pushing changes, detect AI-generated artifacts, draft and improve documentation, generate test plans, and analyze codebases. The marketplace integrates with Amelia for agent-based workflows and Daydream for automated review-fix-test loops, enabling teams to enforce code quality standards consistently across projects.

How to Use

[{"step":1,"action":"Install the Beagle plugin in your Claude Code environment by running `claude plugins install beagle`.","tip":"Ensure you have the latest version of Claude Code (v1.0+) for full compatibility."},{"step":2,"action":"Navigate to your project directory and run `claude beagle review --language python --path ./src --issues security,performance,type-safety`.","tip":"Use `--issues` to filter by specific concerns (e.g., `security`, `memory`, `api-contracts`). Omit to review all areas."},{"step":3,"action":"Review the generated report and address critical issues first. For each issue, use `claude beagle fix --issue-id [ISSUE_ID] --path [FILE_PATH]` to apply suggested fixes.","tip":"Combine Beagle's fixes with manual review for edge cases. Use `claude beagle verify --issue-id [ISSUE_ID]` to re-check resolved issues."},{"step":4,"action":"Integrate Beagle into your CI/CD pipeline by adding a step like `claude beagle review --language go --path ./pkg --min-score 75` to block merges below the threshold.","tip":"Set `--min-score` based on your team's quality bar (e.g., 75 for production, 60 for staging)."},{"step":5,"action":"For frameworks like FastAPI or React, use Beagle's framework-specific presets: `claude beagle review --framework fastapi --path ./app` to enforce best practices.","tip":"Check Beagle's documentation for framework-specific rules (e.g., FastAPI route naming conventions, React prop validation)."}]

Use Cases

Automated Python and FastAPI code review with framework-specific checks

React and TypeScript frontend code review with Tailwind and shadcn/ui support

AI artifact detection to identify code generated by language models

Documentation quality improvement using Diataxis framework

Setup & Installation

Quick Install

No install command available. Check the GitHub repository for manual installation instructions.

Alternative Install (Git Clone)

git clone https://github.com/existential-birds/beagle

Requirements

Claude Code or compatible AI agent
Works with: Claude

Quick Start Guide

Install the Skill

Copy the install command above and run it in your terminal.

Open Your AI Agent

Launch Claude Code, Cursor, or your preferred AI coding agent.

Try It Out

Use the prompt template or examples below to test the skill.

Customize

Adapt the skill to your specific use case and workflow.

Usage Examples

Prompt Template

Use the Beagle plugin to review the [LANGUAGE] code in [REPOSITORY_PATH] for [SPECIFIC_ISSUES]. Focus on [CODE_QUALITY_AREAS] such as [LIST_EXAMPLES]. Provide a summary of findings with actionable recommendations for [TEAM_ROLE].

Example Output

### Beagle Code Review Report
**Repository:** `acme-corp/finance-api` (Python/FastAPI)
**Review Scope:** Core transaction service (`src/transactions/`) and Pydantic models
**Review Date:** 2024-05-15

#### Critical Issues (Fix Immediately)
1. **SQL Injection Risk** in `src/transactions/db.py:127`
   - **Problem:** Raw SQL query uses string formatting (`f"SELECT * FROM {table}"`).
   - **Impact:** Vulnerable to SQL injection if `table` is user-controlled.
   - **Fix:** Use parameterized queries with `execute(table, params)` instead.
   - **Severity:** High (CVSS: 8.2)

2. **Memory Leak** in `src/transactions/worker.py:45`
   - **Problem:** Infinite loop in `process_transactions()` without backoff or rate limiting.
   - **Impact:** Could exhaust memory under high load (tested with 10K transactions).
   - **Fix:** Add `time.sleep(0.1)` between batches and implement circuit breaker.
   - **Severity:** High

#### High-Priority Issues (Address in Next Sprint)
1. **Type Safety** in `src/transactions/schemas.py`
   - **Problem:** Pydantic model `TransactionCreate` uses `Dict[str, Any]` for `metadata`.
   - **Impact:** No validation for nested fields; could lead to runtime errors.
   - **Fix:** Define strict schema for `metadata` using `BaseModel` or `TypedDict`.

2. **Performance Bottleneck** in `src/transactions/utils.py:89`
   - **Problem:** `batch_process()` uses synchronous I/O for database calls.
   - **Impact:** Slows down API response times under concurrent requests (avg: 1.2s → 3.4s).
   - **Fix:** Replace with async `asyncpg` and `aioredis` for database/Redis operations.

#### Recommendations for Team Roles
- **Backend Engineers:** Prioritize SQL injection fix and memory leak in `worker.py`.
- **Data Team:** Review `metadata` schema changes to ensure compatibility with analytics pipelines.
- **DevOps:** Add load testing for `batch_process()` with 100K transactions to validate fixes.

**Next Steps:**
1. Create PRs for critical fixes (target: EOD).
2. Schedule pair programming session for `worker.py` refactor.
3. Update CI/CD to include memory leak detection via `pytest --leaks`.

**Beagle Score:** 68/100 (Improved from 52/100 in last review). Focus areas: security, performance, and type safety.