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Agent Skill · 研究检索

nerua1-ralph(拉尔夫 nerua1)

nerua1-ralph 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。

nerua1-ralph 是研究检索类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为需要联网;许可证为 MIT-0,第三方扫描有提醒项,按安装量在研究检索类的 73,675 个 Skill 里排第 34,118。

总安装 2,274周安装 92GitHub Stars 公开资料未说明下载 714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
1.0.0

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:nerua1-ralph(拉尔夫 nerua1)
来源仓库:https://github.com/nerua1/nerua1-ralph
安装命令:
openclaw skills install nerua1-ralph
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 nerua1-ralph

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。

nerua1-ralph 提供持续循环执行能力,直到任务完成并通过验证。适合需要反复尝试、自动重试或确保结果准确性的自动化流程。可在 OpenClaw 中用于迭代式研究、数据抓取或复杂问题求解。使用前应评估是否会触发长时间运行或资源密集型操作。建议检查来源仓库以确认其适用场景和稳定性。

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 nerua1-ralph;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

    它需要需要联网,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

nerua1-ralph 怎么安装?

在终端执行 openclaw skills install nerua1-ralph。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

nerua1-ralph 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。

nerua1-ralph 需要什么权限?

权限级别是需要联网。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。

nerua1-ralph 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。

nerua1-ralph 用的人多吗?

公开数据是累计安装 2,274 次,近一周安装 92 次,下载 714 次。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。

nerua1-ralph 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

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。

先想清楚的地方

  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 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。

不太适合

  • 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
nerua1-ralph

拉尔夫 nerua1 · 本页

2,274—需要联网MIT-0有提醒

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
description
Persistence loop until task completion with verification - "don't stop until it's done
version
1.0.0
author
Rook (adapted from oh-my-codex)

Ralph Skill for OpenClaw

Self-referential loop that keeps working on a task until it is fully complete and verified. Ralph prevents "almost done" syndrome.

What It Does

Ralph is a persistence wrapper around tasks:

  1. Takes a task that must be completed
  2. Works on it iteratively (up to 10 iterations)
  3. Verifies completion with fresh evidence
  4. If not done → fixes issues and repeats
  5. If done → clean exit

The boulder never stops rolling until it reaches the top.

Usage

/ralph "implement user authentication with JWT tokens"
/ralph "fix all TypeScript errors in src/ directory"
/ralph "write comprehensive tests for the API"

Or say: "ralph", "don't stop", "must complete", "keep going until done"

When to Use

✅ Use Ralph when:

  • Task requires guaranteed completion (not "do your best")
  • Work may span multiple attempts
  • You need verification before declaring done
  • Task has clear completion criteria (tests pass, build succeeds)

❌ Don't use Ralph when:

  • Quick one-shot fix needed
  • You want manual control over completion
  • Task is exploratory (research, planning)

How It Works

The 10-Step Loop

┌─────────────────────────────────────┐
│  1. CONTEXT SNAPSHOT                │
│     Save task state to file         │
├─────────────────────────────────────┤
│  2. REVIEW PROGRESS                 │
│     Check what was done before      │
├─────────────────────────────────────┤
│  3. CONTINUE FROM WHERE LEFT OFF    │
│     Pick up incomplete tasks        │
├─────────────────────────────────────┤
│  4. DELEGATE WORK                   │
│     Route to appropriate agents     │
├─────────────────────────────────────┤
│  5. RUN LONG OPS IN BACKGROUND      │
│     Builds, installs, tests         │
├─────────────────────────────────────┤
│  6. VERIFY COMPLETION               │
│     Fresh evidence required         │
├─────────────────────────────────────┤
│  7. ARCHITECT REVIEW                │
│     Quality verification            │
├─────────────────────────────────────┤
│  8. DESLOP PASS                     │
│     Clean up AI-generated slop      │
├─────────────────────────────────────┤
│  9. REGRESSION CHECK                │
│     Ensure nothing broke            │
├─────────────────────────────────────┤
│  10. DECISION                       │
│     Done → Exit / Not done → Loop   │
└─────────────────────────────────────┘

State Management

Ralph maintains state in ~/.openclaw/state/ralph/:

~/.openclaw/state/ralph/
├── current-task.json       # Active task definition
├── iteration-N/            # Each attempt
│   ├── attempt.log         # What was tried
│   ├── result.json         # Outcome
│   └── evidence/           # Proof of work
└── verification.json       # Final verification

Completion Criteria

Ralph considers task complete ONLY when ALL are true:

  • [ ] All requirements from original task are met
  • [ ] Zero pending TODO items
  • [ ] Fresh test run shows all tests pass
  • [ ] Fresh build shows success
  • [ ] No new errors introduced
  • [ ] Architect verification passed
  • [ ] Post-cleanup regression tests pass

Implementation

#!/bin/bash
# ~/.openclaw/skills/ralph/ralph.sh

TASK="$1"
MAX_ITERATIONS=10
STATE_DIR="$HOME/.openclaw/state/ralph"

# Initialize state
mkdir -p "$STATE_DIR"
TIMESTAMP=$(date +%Y%m%d_%H%M%S)
ITERATION=1

# Save task
cat > "$STATE_DIR/current-task.json" << EOF
{
  "task": "$TASK",
  "started_at": "$TIMESTAMP",
  "max_iterations": $MAX_ITERATIONS,
  "status": "active"
}
EOF

echo "=== RALPH: Starting persistence loop ==="
echo "Task: $TASK"
echo "Max iterations: $MAX_ITERATIONS"
echo ""

while [[ $ITERATION -le $MAX_ITERATIONS ]]; do
  echo "--- Iteration $ITERATION/$MAX_ITERATIONS ---"
  
  # Create iteration directory
  ITER_DIR="$STATE_DIR/iteration-$ITERATION"
  mkdir -p "$ITER_DIR/evidence"
  
  # Step 1-5: Do the work (delegated to main agent)
  echo "Working on task..."
  
  # Step 6: Verify completion
  echo "Verifying completion..."
  
  # Run verification commands
  VERIFICATION_PASSED=true
  
  # Check if tests pass
  if [[ -f "package.json" ]]; then
    if ! npm test > "$ITER_DIR/evidence/test.log" 2>&1; then
      VERIFICATION_PASSED=false
      echo "❌ Tests failed"
    else
      echo "✅ Tests passed"
    fi
  fi
  
  # Check if build succeeds
  if [[ -f "package.json" ]]; then
    if ! npm run build > "$ITER_DIR/evidence/build.log" 2>&1; then
      VERIFICATION_PASSED=false
      echo "❌ Build failed"
    else
      echo "✅ Build succeeded"
    fi
  fi
  
  # Check for TODOs
  TODO_COUNT=$(grep -r "TODO\|FIXME\|XXX" --include="*.ts" --include="*.js" --include="*.py" . 2>/dev/null | wc -l)
  if [[ $TODO_COUNT -gt 0 ]]; then
    echo "⚠️  Found $TODO_COUNT TODO items"
  fi
  
  # Step 7: Decision
  if [[ "$VERIFICATION_PASSED" == true && $TODO_COUNT -eq 0 ]]; then
    echo ""
    echo "=== RALPH: TASK COMPLETE ==="
    echo "Completed in $ITERATION iterations"
    echo "All verification passed"
    
    # Mark complete
    cat > "$STATE_DIR/verification.json" << EOF
{
  "status": "complete",
  "iterations": $ITERATION,
  "completed_at": "$(date +%Y%m%d_%H%M%S)",
  "verification": "passed"
}
EOF
    
    # Clean exit
    /cancel
    exit 0
  fi
  
  # Not complete - save state and continue
  cat > "$ITER_DIR/result.json" << EOF
{
  "iteration": $ITERATION,
  "verification_passed": $VERIFICATION_PASSED,
  "todos_remaining": $TODO_COUNT,
  "timestamp": "$(date +%Y%m%d_%H%M%S)"
}
EOF
  
  echo "Task not complete. Continuing to next iteration..."
  echo ""
  
  ITERATION=$((ITERATION + 1))
done

echo "=== RALPH: MAX ITERATIONS REACHED ==="
echo "Task may need manual intervention"
echo "Check state in: $STATE_DIR"

# Mark as needs help
cat > "$STATE_DIR/verification.json" << EOF
{
  "status": "needs_help",
  "iterations": $MAX_ITERATIONS,
  "completed_at": "$(date +%Y%m%d_%H%M%S)",
  "verification": "incomplete"
}
EOF

exit 1

Integration with OpenClaw

Add to AGENTS.md:

## Persistence Mode

When a task MUST be completed (not "do your best"):

Use `/ralph "<task>"` to activate persistence loop.

Ralph will:
- Keep working until verification passes
- Iterate up to 10 times
- Provide fresh evidence each iteration
- Clean up on completion

Say "cancel" or "stop" to exit early.

Tier System

Ralph uses agent tiers for delegation:

TierUse ForExample
LOWSimple lookups"What does this function return?"
STANDARDNormal work"Add error handling"
THOROUGHComplex analysis"Debug race condition"

Examples

Good Use

User: "ralph implement JWT auth"
→ Ralph loops until:
  - JWT tokens generated correctly
  - Middleware validates tokens
  - Tests pass
  - Build succeeds
→ Clean exit

Bad Use

User: "ralph what do you think about React?"
→ Ralph: "This is exploratory, not completion-based."
→ Use normal conversation instead.

Stop Conditions

Ralph stops when:

  • ✅ All verification passed
  • ❌ User says "stop", "cancel", "abort"
  • ⚠️ Max iterations (10) reached
  • 🚫 Fundamental blocker (missing credentials, external service down)

Output Format

=== RALPH: Starting persistence loop ===
Task: implement JWT auth
Max iterations: 10

--- Iteration 1/10 ---
Working on task...
Verifying completion...
✅ Tests passed
✅ Build succeeded
⚠️  Found 2 TODO items
Task not complete. Continuing...

--- Iteration 2/10 ---
...

=== RALPH: TASK COMPLETE ===
Completed in 3 iterations
All verification passed

Dependencies

  • openclaw CLI
  • Standard POSIX tools
  • Project-specific tools (npm, cargo, etc.)

Version History

  • 1.0.0: Initial implementation based on oh-my-codex ralph skill

平台分布

OpenClaw

91.2%
按下载量换算651

安全审计

VirusTotal

通过

ClawScan

可疑

Static analysis

通过

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

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。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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