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Agent Skill · 研究检索

ralph-mode(拉尔夫模式)

ralph-mode 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。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。

ralph-mode 是研究检索类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为执行命令;许可证为 MIT-0,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 1,149。

总安装 116,413周安装 4,664GitHub Stars 6下载 37,685核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT-0
版本
1.2.0

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-mode(拉尔夫模式)
来源仓库:https://github.com/richginsberg/ralph-mode
安装命令:
openclaw skills install ralph-mode
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。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install ralph-mode

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

具有迭代、背压门和完成标准的自主开发循环。用于需要多次迭代、测试验证和结构化进度跟踪的持续编码会话。通过适用于 OpenClaw 的 Ralph Wiggum 方法,支持 Next.js、Python、FastAPI 和 GPU 工作负载。

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 OpenClaw;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 openclaw skills install ralph-mode;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要执行命令,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

ralph-mode 怎么安装?

在终端执行 openclaw skills install ralph-mode。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

ralph-mode 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

ralph-mode 需要什么权限?

权限级别是执行命令。安装流程涉及命令执行,可能通过 openclaw skills install ralph-mode 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

ralph-mode 是免费的吗?

来源标注的许可证是 MIT-0。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

ralph-mode 用的人多吗?

公开数据是累计安装 116,413 次,近一周安装 4,664 次,下载 37,685 次,GitHub 6 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

ralph-mode 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,商用和分发边界好判断。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 需要执行命令,装到常用环境前要先评估影响面。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 OpenClaw,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。
  • 需要许可证清楚、并且有第三方扫描结果的团队项目。

不太适合

  • 不能接受 Skill 在你机器上执行命令的人。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
ralph-mode

拉尔夫模式 · 本页

116,4136执行命令MIT-0通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

name
ralph-mode
description
Autonomous development loops with iteration, backpressure gates, and completion criteria. Use for sustained coding sessions that require multiple iterations, test validation, and structured progress tracking. Supports Next.js, Python, FastAPI, and GPU workloads with Ralph Wiggum methodology adapted for OpenClaw.

Ralph Mode - Autonomous Development Loops

Ralph Mode implements the Ralph Wiggum technique adapted for OpenClaw: autonomous task completion through continuous iteration with backpressure gates, completion criteria, and structured planning.

When to Use

Use Ralph Mode when:

  • Building features that require multiple iterations and refinement
  • Working on complex projects with acceptance criteria to validate
  • Need automated testing, linting, or typecheck gates
  • Want to track progress across many iterations systematically
  • Prefer autonomous loops over manual turn-by-turn guidance

Core Principles

Three-Phase Workflow

Phase 1: Requirements Definition

  • Document specs in specs/ (one file per topic of concern)
  • Define acceptance criteria (observable, verifiable outcomes)
  • Create implementation plan with prioritized tasks

Phase 2: Planning

  • Gap analysis: compare specs against existing code
  • Generate IMPLEMENTATION_PLAN.md with prioritized tasks
  • No implementation during this phase

Phase 3: Building (Iterative)

  • Pick one task from plan per iteration
  • Implement, validate, update plan, commit
  • Continue until all tasks complete or criteria met

Backpressure Gates

Reject incomplete work automatically through validation:

Programmatic Gates (Always use these):

  • Tests: [test command] - Must pass before committing
  • Typecheck: [typecheck command] - Catch type errors early
  • Lint: [lint command] - Enforce code quality
  • Build: [build command] - Verify integration

Subjective Gates (Use for UX, design, quality):

  • LLM-as-judge reviews for tone, aesthetics, usability
  • Binary pass/fail - converges through iteration
  • Only add after programmatic gates work reliably

Context Efficiency

  • One task per iteration = fresh context each time
  • Spawn sub-agents for exploration, not main context
  • Lean prompts = smart zone (~40-60% utilization)
  • Plans are disposable - regenerate cheap vs. salvage

File Structure

Create this structure for each Ralph Mode project:

project-root/
├── IMPLEMENTATION_PLAN.md     # Shared state, updated each iteration
├── AGENTS.md                  # Build/test/lint commands (~60 lines)
├── specs/                     # Requirements (one file per topic)
│   ├── topic-a.md
│   └── topic-b.md
├── src/                        # Application code
└── src/lib/                    # Shared utilities

IMPLEMENTATION_PLAN.md

Priority task list - single source of truth. Format:

# Implementation Plan

## In Progress
- [ ] Task name (iteration N)
  - Notes: discoveries, bugs, blockers

## Completed
- [x] Task name (iteration N)

## Backlog
- [ ] Future task

Topic Scope Test

Can you describe the topic in one sentence without "and"?

  • ✅ "User authentication with JWT and session management"
  • ❌ "Auth, profiles, and billing" → 3 topics

AGENTS.md - Operational Guide

Succinct guide for running the project. Keep under 60 lines:

# Project Operations

## Build Commands
npm run dev      # Development server
npm run build     # Production build

## Validation
npm run test      # All tests
npm run lint      # ESLint
npm run typecheck  # TypeScript
npm run e2e       # E2E tests

## Operational Notes
- Tests must pass before committing
- Typecheck failures block commits
- Use existing utilities from src/lib over ad-hoc copies

Hats (Personas)

Specialized roles for different tasks:

Hat: Architect (@architect)

  • High-level design, data modeling, API contracts
  • Focus: patterns, scalability, maintainability

Hat: Implementer (@implementer)

  • Write code, implement features, fix bugs
  • Focus: correctness, performance, test coverage

Hat: Tester (@tester)

  • Test authoring, validation, edge cases
  • Focus: coverage, reliability, reproducibility

Hat: Reviewer (@reviewer)

  • Code reviews, PR feedback, quality assessment
  • Focus: style, readability, adherence to specs

Usage:

"Spawn a sub-agent with @architect hat to design the data model"

Loop Mechanics

Outer Loop (You coordinate)

Your job as main agent: engineer setup, observe, course-correct.

  1. Don't allocate work to main context - Spawn sub-agents
  2. Let Ralph Ralph - LLM will self-identify, self-correct
  3. Use protection - Sandbox is your security boundary
  4. Plan is disposable - Regenerate when wrong/stale
  5. Move outside the loop - Sit and watch, don't micromanage

Inner Loop (Sub-agent executes)

Each sub-agent iteration:

  1. Study - Read plan, specs, relevant code
  2. Select - Pick most important uncompleted task
  3. Implement - Write code, one task only
  4. Validate - Run tests, lint, typecheck (backpressure)
  5. Update - Mark task done, note discoveries, commit
  6. Exit - Next iteration starts fresh

Stopping Conditions

Loop ends when:

  • ✅ All IMPLEMENTATION_PLAN.md tasks completed
  • ✅ All acceptance criteria met
  • ✅ Tests passing, no blocking issues
  • ⚠️ Max iterations reached (configure limit)
  • 🛑 Manual stop (Ctrl+C)

Completion Criteria

Define success upfront - avoid "seems done" ambiguity.

Programmatic (Measurable)

  • All tests pass: [test_command] returns 0
  • Typecheck passes: No TypeScript errors
  • Build succeeds: Production bundle created
  • Coverage threshold: e.g., 80%+

Subjective (LLM-as-Judge)

For quality criteria that resist automation:

## Completion Check - UX Quality
Criteria: Navigation is intuitive, primary actions are discoverable
Test: User can complete core flow without confusion

## Completion Check - Design Quality
Criteria: Visual hierarchy is clear, brand consistency maintained
Test: Layout follows established patterns

Run LLM-as-judge sub-agent for binary pass/fail.

Technology-Specific Patterns

Next.js Full Stack

specs/
├── authentication.md
├── database.md
└── api-routes.md

src/
├── app/                    # App Router
├── components/              # React components
├── lib/                    # Utilities (db, auth, helpers)
└── types/                   # TypeScript types

AGENTS.md:
  Build: npm run dev
  Test: npm run test
  Typecheck: npx tsc --noEmit
  Lint: npm run lint

Python (Scripts/Notebooks/FastAPI)

specs/
├── data-pipeline.md
├── model-training.md
└── api-endpoints.md

src/
├── pipeline.py
├── models/
├── api/
└── tests/

AGENTS.md:
  Build: python -m src.main
  Test: pytest
  Typecheck: mypy src/
  Lint: ruff check src/

GPU Workloads

specs/
├── model-architecture.md
├── training-data.md
└── inference-pipeline.md

src/
├── models/
├── training/
├── inference/
└── utils/

AGENTS.md:
  Train: python train.py
  Test: pytest tests/
  Lint: ruff check src/
  GPU Check: nvidia-smi

Quick Start Command

Start a Ralph Mode session:

"Start Ralph Mode for my project at ~/projects/my-app. I want to implement user authentication with JWT.

I will:

  1. Create IMPLEMENTATION_PLAN.md with prioritized tasks
  2. Spawn sub-agents for iterative implementation
  3. Apply backpressure gates (test, lint, typecheck)
  4. Track progress and announce completion

Operational Learnings

When Ralph patterns emerge, update AGENTS.md:

## Discovered Patterns

- When adding API routes, also add to OpenAPI spec
- Use existing db utilities from src/lib/db over direct calls
- Test files must be co-located with implementation

Escape Hatches

When trajectory goes wrong:

  • Ctrl+C - Stop loop immediately
  • Regenerate plan - "Discard IMPLEMENTATION_PLAN.md and re-plan"
  • Reset - "Git reset to last known good state"
  • Scope down - Create smaller scoped plan for specific work

Advanced: LLM-as-Judge Fixture

For subjective criteria (tone, aesthetics, UX):

Create src/lib/llm-review.ts:

interface ReviewResult {
  pass: boolean;
  feedback?: string;
}

async function createReview(config: {
  criteria: string;
  artifact: string; // text or screenshot path
}): Promise<ReviewResult>;

Sub-agents discover and use this pattern for binary pass/fail checks.

Critical Operational Requirements

Based on empirical usage, enforce these practices to avoid silent failures:

1. Mandatory Progress Logging

Ralph MUST write to PROGRESS.md after EVERY iteration. This is non-negotiable.

Create PROGRESS.md in project root at start:

# Ralph: [Task Name]

## Iteration [N] - [Timestamp]

### Status
- [ ] In Progress | [ ] Blocked | [ ] Complete

### What Was Done
- [Item 1]
- [Item 2]

### Blockers
- None | [Description]

### Next Step
[Specific next task from IMPLEMENTATION_PLAN.md]

### Files Changed
- `path/to/file.ts` - [brief description]

Why: External observers (parent agents, crons, humans) can tail one file instead of scanning directories or inferring state from session logs.

2. Session Isolation & Cleanup

Before spawning a new Ralph session:

  • Check for existing Ralph sub-agents via sessions_list
  • Kill or verify completion of previous sessions
  • Do NOT spawn overlapping Ralph sessions on same codebase

Anti-pattern: Spawning Ralph v2 while v1 is still running = file conflicts, race conditions, lost work.

3. Explicit Path Verification

Never assume directory structure. At start of each iteration:

// Verify current working directory
const cwd = process.cwd();
console.log(`Working in: ${cwd}`);

// Verify expected paths exist
if (!fs.existsSync('./src/app')) {
  console.error('Expected ./src/app, found:', fs.readdirSync('.'));
  // Adapt or fail explicitly
}

Why: Ralph may be spawned from different contexts with different working directories.

4. Completion Signal Protocol

When done, Ralph MUST:

  1. Write final PROGRESS.md with "## Status: COMPLETE"
  2. List all created/modified files
  3. Exit cleanly (no hanging processes)

Example completion PROGRESS.md:

# Ralph: Influencer Detail Page

## Status: COMPLETE ✅

**Finished:** [ISO timestamp]

### Final Verification
- [x] TypeScript: Pass
- [x] Tests: Pass  
- [x] Build: Pass

### Files Created
- `src/app/feature/page.tsx`
- `src/app/api/feature/route.ts`

### Testing Instructions
1. Run: `npm run dev`
2. Visit: `http://localhost:3000/feature`
3. Verify: [specific checks]

5. Error Handling Requirements

If Ralph encounters unrecoverable errors:

  1. Log to PROGRESS.md with "## Status: BLOCKED"
  2. Describe blocker in detail
  3. List attempted solutions
  4. Exit cleanly (don't hang)

Do not silently fail. A Ralph that stops iterating with no progress log is indistinguishable from one still working.

6. Iteration Time Limits

Set explicit iteration timeouts:

## Operational Parameters
- Max iteration time: 10 minutes
- Total session timeout: 60 minutes
- If iteration exceeds limit: Log blocker, exit

Why: Prevents infinite loops on stuck tasks, allows parent agent to intervene.

Memory Updates

After each Ralph Mode session, document:

## [Date] Ralph Mode Session

**Project:** [project-name]
**Duration:** [iterations]
**Outcome:** success / partial / blocked
**Learnings:**
- What worked well
- What needs adjustment
- Patterns to add to AGENTS.md

Appendix: Hall of Failures

Common anti-patterns observed:

Anti-PatternConsequencePrevention
No progress loggingParent agent cannot determine statusMandatory PROGRESS.md
Silent failureWork lost, time wastedExplicit error logging
Overlapping sessionsFile conflicts, corrupt stateCheck/cleanup before spawn
Path assumptionsWrong directory, wrong filesExplicit verification
No completion signalParent waits indefinitelyClear COMPLETE status
Infinite iterationResource waste, no progressTime limits + blockers
Complex initial promptsSub-agent never starts (empty session logs)SIMPLIFY instructions

NEW: Session Initialization Best Practices (2025-02-07)

Problem: Sub-agents spawn but don't execute

Evidence: Empty session logs (2 bytes), no tool calls, 0 tokens used

Root Causes

  1. Instructions too complex - Overwhelms isolated session initialization
  2. No clear execution trigger - Agent doesn't know to start
  3. Branching logic - "If X do Y, if Z do W" confuses task selection
  4. Multiple files mentioned - Can't decide which to start with

Fix: SIMPLIFIED Ralph Task Template

## Task: [ONE specific thing]

**File:** exact/path/to/file.ts
**What:** Exact description of change
**Validate:** Exact command to run
**Then:** Update PROGRESS.md and exit

## Rules
1. Do NOT look at other files
2. Do NOT "check first"
3. Make the change, validate, exit

BEFORE (Bad - causes stalls):

Fix all TypeScript errors across these files:
- lib/db.ts has 2 errors
- lib/proposal-service.ts has 5 errors
- route.ts has errors
Check which ones to fix first, then...

AFTER (Good - executes):

Fix lib/db.ts line 27:
Change: PoolClient to pg.PoolClient
Validate: npm run typecheck
Exit immediately after

CRITICAL: Single File Rule

Each Ralph iteration gets ONE file. Not "all errors", not "check then decide". ONE file, ONE change, validate, exit.

CRITICAL: Update PROGRESS.md

MANDATORY: After EVERY iteration, update PROGRESS.md with:

## Iteration [N] - [Timestamp]

### Status: Complete ✅ | Blocked ⛔ | Failed ❌

### What Was Done
- [Specific changes made]

### Validation
- [Test/lint/typecheck results]

### Next Step
- [What should happen next]

Why this matters: Cron job reads PROGRESS.md for status updates. If not updated, status appears stale/repetitive.

Debugging Ralph Stalls

If Ralph stalls:

  1. Check session logs (should show tool calls within 60s)
  2. If empty after spawn → instructions too complex
  3. Reduce: ONE file, ONE line number, ONE change
  4. Shorter timeout forces smaller tasks (300s not 600s)

Fixing Stale Status Reports

If cron reports same status repeatedly:

  1. Check PROGRESS.md was updated by sub-agent
  2. If not updated → sub-agent skipped documentation step
  3. Update skill: Add "MANDATORY PROGRESS.md update" to prompt
  4. Manual fix: Update PROGRESS.md to reflect actual state

Summary

Ralph works when: Single file focus + explicit change + validate + exit Ralph stalls when: Complex decisions + multiple files + conditional logic

平台分布

OpenClaw

73.27%
按下载量换算27,612

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

未展示

权限和风险

执行命令

安装流程涉及命令执行,可能通过 openclaw skills install ralph-mode 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。目前只有一个公开来源,建议同时核对源仓库。

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