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remote-skill-engine远程技能引擎

Agent Skill

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。

总安装

18,252

周安装

784

GitHub Stars

2

下载量

6,397
OpenClaw

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

2

许可证

MIT-0

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: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

简介

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。

SKILL.md

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. 🌐⚡

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

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

能力 5

展示第三方安全扫描或审计结果

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

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

external-service

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 warning/failed 结果,不能写成本站确认安全。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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