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ralph-loop-guide拉尔夫循环指南

Agent Skill

ralph-loop-guide 用于记录任务执行中的错误、用户纠正、经验和能力缺口,适合在 Codex、Claude、Cursor、Gemini CLI 中希望让 Agent 持续沉淀问题、修正和最佳实践时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

306

周安装

13

GitHub Stars

134

下载量

107
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

3

许可证

MIT

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:ralph-loop-guide(拉尔夫循环指南)
来源仓库:https://github.com/anton-abyzov/specweave
仓库路径:skills/ralph-loop-guide
安装命令:
npx skills add https://github.com/anton-abyzov/specweave --skill ralph-loop-guide
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。不同来源提供的安装方式可能略有差异;本站展示可直接复制的安装命令,安装前请核对来源页面。

skills.shnpx skills
npx skills add https://github.com/anton-abyzov/specweave --skill ralph-loop-guide

简介

用于记录任务执行中的错误、用户纠正和经验缺口。

  • 适合让 Agent 持续沉淀问题、修正和最佳实践。
  • 可结合来源仓库和原始 README 核验具体用法。
  • 安装前建议确认权限范围和维护状态,避免触发联网或文件读写。
  • ralph-loop-guide 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

Ralph Loop Best Practices Guide

This skill provides guidelines for effective autonomous iteration using the Ralph Wiggum pattern, based on Anthropic's official ralph-loop plugin.

How Ralph Loop Works

The Ralph Loop is a methodology for iterative AI development through self-referential feedback loops:

  1. The prompt never changes between iterations
  2. Claude's previous work persists in files
  3. Each cycle, the AI sees modified files and git history
  4. Enables autonomous refinement without manual re-prompting

Effective Ralph Prompt Design

Required Elements

  1. Clear Completion Signal ## Completion Criteria - [] All unit tests pass (npm test) - [] Build succeeds (npm run build) - [] Coverage ≥80% (npm run coverage) - [] No TypeScript errors (npx tsc --noEmit) When ALL criteria are met, output: "RALPH_COMPLETE: All tasks done"
  2. Incremental Phases ## Implementation Phases ### Phase 1: Foundation - Create database schema - Set up repository layer - Write unit tests for repository ### Phase 2: Business Logic - Implement service layer - Add validation - Write service tests ### Phase 3: API Layer - Create endpoints - Add input validation - Write API tests - Run full test suite
  3. Self-Correction Cycles ` ## On Each Iteration 1. Run tests: npm test 2. If tests fail: - Read error messages - Fix the failing code - Run tests again 3. If tests pass: - Check coverage: npm run coverage - If coverage < 80%, add more tests - If coverage ≥ 80%, proceed to next phase `
  4. Safety Limits ## Safety Rules - Maximum 100 iterations per phase - If stuck for 5 iterations on same error, ask for help - Never delete test files - Always commit working state before major changes

Good Ralph Prompts

Example 1: API Development

# Task: Build User Authentication API

## Context
- Node.js + Express + TypeScript
- PostgreSQL with Prisma
- JWT authentication

## Phases

### Phase 1: Database (iterations 1-10)
Create Prisma schema for User model with:
- id, email (unique), passwordHash, createdAt, updatedAt

Run: `npx prisma migrate dev`
Test: Schema validates with `npx prisma validate`

### Phase 2: Repository (iterations 11-25)
Create UserRepository with:
- create(email, password) → User
- findByEmail(email) → User | null
- findById(id) → User | null

Tests: All repository tests pass

### Phase 3: Service (iterations 26-45)
Create AuthService with:
- register(email, password) → { user, token }
- login(email, password) → { user, token }
- validateToken(token) → User

Tests: All service tests pass

### Phase 4: Routes (iterations 46-70)
Create routes:
- POST /auth/register
- POST /auth/login
- GET /auth/me (protected)

Tests: All API tests pass with supertest

### Phase 5: Integration (iterations 71-100)
- Full E2E flow works
- Error handling for all edge cases
- Rate limiting on auth endpoints

## Completion
When `npm test` passes with 0 failures AND coverage ≥80%,
output: "RALPH_COMPLETE"

Example 2: Refactoring Task

# Task: Refactor Legacy Auth Module

## Current State
- Monolithic auth.js with 500 lines
- No tests
- Mixed concerns

## Target State
- Separate files: auth-service.ts, user-repository.ts, token-utils.ts
- 100% backward compatible
- 80%+ test coverage

## Iteration Loop

1. Read current auth.js
2. Identify one function to extract
3. Create new file with extracted function
4. Update imports in auth.js
5. Run existing integration tests
6. If tests fail, fix and retry
7. If tests pass, proceed to next function

## Completion Criteria
- [ ] auth.js < 100 lines
- [ ] All functions have dedicated files
- [ ] All tests pass
- [ ] No breaking changes to API

Output "RALPH_COMPLETE" when done.

When Ralph Works

Task TypeSuitabilityReason
API development✅ ExcellentClear test-driven feedback
Refactoring✅ ExcellentTests verify each step
Bug fixing✅ GoodReproduce → fix → verify cycle
Test writing✅ GoodCoverage metrics as feedback
Documentation⚠️ LimitedNo automated verification
UI development⚠️ LimitedVisual verification hard
Design decisions❌ PoorRequires human judgment
One-time scripts❌ PoorNo iteration benefit

When NOT to Use Ralph

  1. Subjective decisions - No objective completion signal
  2. One-time operations - No benefit from iteration
  3. Ambiguous requirements - Will spin without progress
  4. Security-critical code - Needs human review
  5. Production deployments - Too risky for autonomous action

Anti-Patterns to Avoid

1. Vague Completion Criteria

# BAD
Complete when the code looks good.

# GOOD
Complete when:
- npm test exits with code 0
- npm run build succeeds
- No TypeScript errors (npx tsc --noEmit)

2. No Phase Boundaries

# BAD
Build the entire application.

# GOOD
Phase 1: Database schema (test: migrations apply)
Phase 2: Repository layer (test: unit tests pass)
Phase 3: Service layer (test: integration tests pass)

3. Missing Error Recovery

# BAD
If something fails, figure it out.

# GOOD
If tests fail:
1. Read the error message
2. Identify the failing file:line
3. Fix the specific issue
4. Run tests again
5. If same error after 3 attempts, try alternative approach

4. No Safety Limits

# BAD
Keep going until done.

# GOOD
- Max 100 iterations total
- Max 10 retries per failing test
- Checkpoint every 25 iterations

Integration with SpecWeave

SpecWeave's /sw:auto command implements Ralph Loop with:

  1. Tasks.md as Completion Checklist

- Each [] pending task is a completion criterion - Auto mode continues until all [x] completed

  1. Built-in Quality Gates

- --build - Build must pass - --tests - Tests must pass - --e2e - E2E tests must pass - --cov N - Coverage threshold

  1. Automatic Phase Management

- Tasks grouped by User Story - Progress tracked in metadata.json - External sync keeps stakeholders informed

Real-World Success Stories

From Anthropic's documentation:

  • "6 repositories overnight"
  • "$50k contract for $297 in API costs"
  • "259 PRs, 497 commits, 40,000 lines in one month without opening IDE"

The key to success: Well-defined tasks with automated verification.

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

04

需要参考平台分布和安装热度时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Claude Code

26.83%
按下载量换算29

Cursor

23.93%
按下载量换算26

OpenCode

19.92%
按下载量换算21

Codex

13.78%
按下载量换算15

Antigravity

7.88%
按下载量换算8

Gemini CLI

3.86%
按下载量换算4

安全审计

暂无安全审计结果可展示。

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

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