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Agent Skill · 研究检索

remote-skill-engine(远程技能引擎)

remote-skill-engine 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。

remote-skill-engine 是研究检索类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为调用外部服务;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 7,707。

总安装 18,252周安装 784GitHub Stars 2下载 6,397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:remote-skill-engine(远程技能引擎)
来源仓库:https://github.com/oki3505f/remote-skill-engine
安装命令:
openclaw skills install remote-skill-engine
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 remote-skill-engine

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。

缓存并使用来自 ClawHub 和 GitHub 的技能,就像本地安装一样。将远程技能存储在本地缓存文件夹中以供离线使用。

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 remote-skill-engine;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

    它需要调用外部服务,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

remote-skill-engine 怎么安装?

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

remote-skill-engine 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。

remote-skill-engine 需要什么权限?

权限级别是调用外部服务。该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

remote-skill-engine 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。

remote-skill-engine 用的人多吗?

公开数据是累计安装 18,252 次,近一周安装 784 次,下载 6,397 次,GitHub 2 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。

remote-skill-engine 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
remote-skill-engine

远程技能引擎 · 本页

18,2522调用外部服务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
remote-skill-engine
description
Cache and use skills from ClawHub and GitHub as if locally installed. Stores remote skills in local cache folder for offline use.

Remote Skill Engine

This skill enables you to discover, cache, and use skills directly from remote registries (ClawHub, GitHub, etc.). Skills are stored in ~/.openclaw/workspace/remote-skills-cache/ and work exactly like locally installed skills.

Core Capabilities

1. Skill Discovery & Search

Search across multiple registries:

# ClawHub search
clawhub search "<query>" --limit <n>

# GitHub skill search (via gh CLI)
gh search repos --language=markdown "skill openclaw" "<topic>"

When to use: User needs a skill for a specific task, wants to explore available skills, or needs to compare options.

2. Remote Skill Caching (KEY FEATURE)

Cache any remote skill to work EXACTLY like installed skills:

# Cache a skill from ClawHub
./scripts/cache-skill.sh clawhub://security-auditor

# Cache from GitHub
./scripts/cache-skill.sh github://owner/repo/branch

# Cache from direct URL
./scripts/cache-skill.sh https://raw.githubusercontent.com/.../SKILL.md

# List cached skills
clawhub list --cache

# Use cached skill (works like installed!)
# Just trigger it normally - it's in your skills path!

Cache Location: ~/.openclaw/workspace/remote-skills-cache/<skill-name>/

Cached skills are symlinked to skills/ folder so they work identically to installed skills.

3. Batch Cache Management

# Cache multiple skills at once
./scripts/cache-skills-batch.json skills-list.json

# Update all cached skills
./scripts/update-cached-skills.sh

# Remove cached skill
./scripts/uncache-skill.sh <skill-name>

# Show cache stats
./scripts/cache-stats.sh

4. Smart Sync & Updates

# Check for updates to cached skills
./scripts/check-updates.sh

# Sync specific skill to latest
./scripts/sync-skill.sh <skill-name>

# Auto-sync on skill trigger (configurable)
# Set in config.json: {"autoSync": true}

5. Offline Mode

Once cached, skills work WITHOUT internet:

  • All scripts available locally
  • References cached alongside SKILL.md
  • Assets downloaded and stored
  • No network calls needed

Workflows

NEW: Workflow 1 - Cache Remote Skill

Trigger: User says "Install/caching <skill-name>" or "Get <skill> from web"

# Step 1: Find the skill
clawhub search "<skill-name>" --limit 1

# Step 2: Cache it locally
python scripts/cache-skill.py <skill-name> <source-url>

# Step 3: Verify cache
ls ~/.openclaw/workspace/remote-skills-cache/<skill-name>/

# Step 4: Use it (works like installed!)
# Just use the skill normally - it auto-triggers from skills/

NEW: Workflow 2 - Batch Cache Skills List

Trigger: User wants multiple skills cached

// skills-to-cache.json
{
  "skills": [
    {"name": "security-auditor", "source": "clawhub://security-auditor"},
    {"name": "coding-agent", "source": "github://user/repo/main"}
  ]
}
./scripts/batch-cache.sh skills-to-cache.json

Workflow 3: Compare Multiple Skills (Enhanced)

Trigger: User says "Which skill is better for X?"

  1. Fetch metadata for each skill
  2. Check if cached, cache if not
  3. Create comparison with SOURCE + CACHE STATUS:
   | Skill | Version | Source | Cached | Last Sync |
   |-------|---------|--------|--------|-----------|
   | skill-a | 1.0.0 | ClawHub | ✅ | 2h ago |
   | skill-b | 2.1.0 | GitHub | ❌ | - |
  1. Recommend + offer to cache

Workflow 4: Sync Cached Skills

Trigger: Heartbeat or user says "Update cached skills"

# Check all cached skills for updates
./scripts/check-updates.sh

# Update outdated skills
./scripts/update-cached-skills.sh --auto

# Update specific skill
./scripts/sync-skill.sh <skill-name>

Workflow 5: Use Cached Skill (Transparent)

Trigger: User triggers any cached skill normally

  • Skill is already in skills/ folder (symlinked)
  • Works IDENTICALLY to installed skills
  • No special handling needed
  • All scripts/refs/assets available locally

Scripts

scripts/fetch-skill.py

Fetch a skill's SKILL.md and parse frontmatter without full download.

#!/usr/bin/env python3
"""Fetch remote skill metadata without full download."""
import requests
import yaml
import sys

def fetch_skill_frontmatter(skill_url):
    """Fetch only YAML frontmatter from SKILL.md"""
    resp = requests.get(skill_url, stream=True)
    content = ""
    in_frontmatter = False
    for line in resp.iter_lines():
        line = line.decode('utf-8')
        if line == '---':
            if not in_frontmatter:
                in_frontmatter = True
                continue
            else:
                break
        if in_frontmatter:
            content += line + '\
'
    
    try:
        return yaml.safe_load(content)
    except yaml.YAMLError as e:
        print(f"Parse error: {e}", file=sys.stderr)
        return None

if __name__ == "__main__":
    if len(sys.argv) != 2:
        print("Usage: fetch-skill.py <skill-url>")
        sys.exit(1)
    
    metadata = fetch_skill_frontmatter(sys.argv[1])
    if metadata:
        print(f"Name: {metadata.get('name', 'N/A')}")
        print(f"Description: {metadata.get('description', 'N/A')}")

Usage:

python scripts/fetch-skill.py "https://raw.githubusercontent.com/repo/SKILL.md"

scripts/compare-skills.py

Compare multiple skills side-by-side.

#!/usr/bin/env python3
"""Compare multiple remote skills."""
import json
import sys

def compare_skills(skill_data_list):
    """Generate comparison table"""
    print("| Skill | Version | Description | Requirements |")
    print("|-------|---------|-------------|--------------|")
    for skill in skill_data_list:
        name = skill.get('name', 'N/A')
        version = skill.get('version', 'N/A')
        desc = skill.get('description', '')[:80] + '...' if len(skill.get('description', '')) > 80 else skill.get('description', 'N/A')
        reqs = skill.get('requires', 'None')
        print(f"| {name} | {version} | {desc} | {reqs} |")

if __name__ == "__main__":
    # Read JSON from stdin
    skills = json.load(sys.stdin)
    compare_skills(skills)

References

references/registry-urls.md

Known skill registry endpoints:

ClawHub
  • Search: https://clawhub.com/api/skills/search?q=<query>
  • Skill detail: https://clawhub.com/api/skills/<name>
  • Raw SKILL.md: https://raw.githubusercontent.com/<owner>/<repo>/SKILL.md
GitHub
  • Search API: https://api.github.com/search/code?q=SKILL.md+openclaw
  • Raw file: https://raw.githubusercontent.com/<owner>/<repo>/<branch>/SKILL.md
Awesome Lists
  • https://raw.githubusercontent.com/openclaw/awesome-openclaw/main/README.md

references/skill-patterns.md

Common skill patterns to recognize:

Skill Types:

  • Tool wrappers - Provide CLI access to external tools (nmap, sqlmap, etc.)
  • Workflow engines - Multi-step processes (security audits, deployments)
  • Knowledge bases - Domain expertise + reference docs
  • Automation scripts - Repetitive task automation
  • Integration layers - MCP servers, API connectors

Metadata Patterns:

metadata:
  openclaw:
    requires:
      bins: ["tool-name"]  # Required binaries
    install:
      - kind: node  # or brew, apt, pip
        package: package-name

Usage Examples

Example 1: Find and Use Security Skill

User: "Find me a skill for web security scanning"

You:
1. clawhub search "web security" --limit 5
2. Present results
3. User picks "security-audit-toolkit"
4. Fetch SKILL.md, read workflows
5. Follow the skill's security audit process

Example 2: Temporary Skill Usage

User: "Use the coding agent to review my repo, but don't install it"

You:
1. Fetch coding agent SKILL.md from ClawHub
2. Read its code review workflow
3. Execute the workflow steps manually
4. Report findings

Example 3: Batch Discovery

User: "Show me all available skills"

You:
1. clawhub search "" --limit 100
2. Categorize by keywords
3. Present organized list:
   - Security (12 skills)
   - Coding (8 skills)
   - Automation (6 skills)
   - etc.

Best Practices

  1. Cache metadata locally - Store skill descriptions in memory/skills-cached.md to avoid repeated fetches
  2. Respect rate limits - Don't hammer ClawHub/GitHub APIs
  3. Verify skill sources - Only fetch from trusted registries
  4. Clean up temp files - Remove /tmp/remote-skill-* after use
  5. Track skill usage - Log which remote skills work well for future reference

Trigger Examples

When this skill activates:

  • "Find a skill for X"
  • "What skills do Y?"
  • "Use <skill-name> without installing"
  • "Compare skills for X"
  • "Show me available skills"
  • "What does <skill> do?"
  • "Is there a skill for X?"

Remote Skill Engine - Stream skills, don't install them. 🌐⚡

平台分布

OpenClaw

87.72%
按下载量换算5,611

安全审计

VirusTotal

可疑

ClawScan

可疑

Static analysis

未展示

权限和风险

调用外部服务

该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

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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