🧪 Skills

Skill Explorer

Systematically discover, evaluate, compare, and assess OpenClaw skills to find the right, safe, and high-quality option for your specific task.

v1.0.0
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Description

skill-explorer

A systematic framework for discovering, evaluating, and comparing OpenClaw skills. Use when you need to find the right skill for a specific task, compare multiple options, or assess skill quality and safety.

Overview

This skill provides a battle-tested workflow for skill exploration:

  1. Demand Analysis → Clarify what you need
  2. Search & Discovery → Find relevant skills
  3. Information Gathering → Collect metrics and details
  4. Lateral Exploration → Find alternatives and competitors
  5. Deep Dive → Download and inspect skill files
  6. Safety Assessment → Security review
  7. Synthesis & Report → Output comparison and recommendations
  8. Decision Support → Present options for user approval

When to Use This Skill

Use skill-explorer when:

  • You need to find a skill for a specific task
  • You want to compare multiple similar skills
  • You need to evaluate skill quality before installation
  • You're doing security review of a skill
  • You want to discover related or complementary skills

The Exploration Workflow

Phase 1: Demand Analysis

Clarify the requirements:

What task does the user need to accomplish?
What are the must-have vs nice-to-have features?
Any constraints (budget, platform, language)?
What's the priority: functionality, popularity, or safety?

Document the search criteria:

  • Primary keywords
  • Secondary/alternative terms
  • Platform constraints (e.g., "must work with Chinese market")
  • Safety requirements (e.g., "no network access")

Phase 2: Search & Discovery

Primary search:

clawhub search <primary-keyword>
clawhub search <related-term-1> <related-term-2>

Capture initial results: Record top 5-10 results with:

  • Skill name
  • Relevance score
  • First impression of summary

Phase 3: Information Gathering

For each promising skill, collect:

clawhub inspect <skill-name> --json

Extract key metrics:

Metric Why It Matters
stats.stars Community quality indicator
stats.downloads Popularity/visibility
stats.installsAllTime Actual adoption
stats.installsCurrent Active usage (low churn = good)
stats.versions Maintenance activity
owner.handle Developer reputation
updatedAt Freshness

Read SKILL.md:

  • Core functionality
  • Use cases
  • Prerequisites
  • Integration requirements

Phase 4: Lateral Exploration

Find alternatives and complements:

# Search with related keywords
clawhub search <alternative-keyword-1>
clawhub search <alternative-keyword-2>

# Look for broader/narrower skills
clawhub search <broader-category>
clawhub search <specific-subtask>

Expand the candidate pool:

  • Direct competitors (same function)
  • Partial overlaps (related function)
  • Complementary skills (work together)
  • Domain-specific variants (e.g., "CN" versions)

Phase 5: Deep Dive

Download and inspect promising skills:

# Install to temp directory for inspection
cd /tmp && mkdir skill-check
cd skill-check && clawhub install <skill-name>

File structure analysis:

find . -type f | sort

Look for:

  • SKILL.md - Main documentation
  • scripts/ - Executable code
  • package.json / requirements.txt - Dependencies
  • _meta.json - Metadata
  • Hidden files or unusual structures

Phase 6: Safety Assessment

Static code analysis:

# Check for suspicious patterns
grep -r -E "(eval\(|exec\(|Function\(|atob\(|btoa\()" .
grep -r -E "(crypto|encrypt|decrypt|base64|0x[0-9a-f]{20,})" .

# Check for network/API calls
grep -r -E "(https?://|api\.|token|key|secret|password)" .

# Check for file system operations
grep -r -E "(fs\.|writeFile|readFile|unlink|chmod)" .

Risk classification:

Level Indicators
🟢 Low Pure documentation, no scripts, no network
🟡 Medium Scripts but official APIs only, read-only ops
🔴 High Obfuscated code, unknown network endpoints, write operations

Special checks:

  • VirusTotal warnings (verify if false positive)
  • Hardcoded credentials or tokens
  • External dependencies (npm/pip packages)
  • Permission requirements (camera, microphone, etc.)

Phase 7: Synthesis & Report

Create comparison table:

| Skill | Stars | Installs | Safety | Best For |
|-------|-------|----------|--------|----------|
| skill-a | ⭐⭐ 25 | 45 | 🟢 | General use |
| skill-b | ⭐ 8 | 12 | 🟢 | Specific niche |
| skill-c | ⭐⭐⭐ 60 | 120 | 🟡 | Power users |

Write detailed analysis:

  1. Executive Summary - Top 2-3 recommendations
  2. Detailed Comparison - Feature-by-feature analysis
  3. Safety Assessment - Security findings
  4. Use Case Mapping - Which skill fits which scenario
  5. Installation Guide - Prerequisites and steps

Phase 8: Decision Support

Present clear options:

## Recommendation

### Option A: Best Overall → [skill-name]
- Why: Highest quality + safety
- Trade-off: May lack advanced features

### Option B: Most Popular → [skill-name]
- Why: Community validated
- Trade-off: Higher complexity

### Option C: Specific Need → [skill-name]
- Why: Perfect fit for [specific use case]
- Trade-off: Less generalizable

Get user approval:

  • Present options with trade-offs
  • Ask for priority (functionality vs safety vs popularity)
  • Wait for explicit approval before installation
  • Document approved skills for installation queue

Best Practices

Do's

  • ✅ Always check multiple similar skills (don't settle for first result)
  • ✅ Download and inspect before recommending installation
  • ✅ Document security findings clearly
  • ✅ Consider the user's specific context (language, platform, expertise)
  • ✅ Update EVOLUTION.md after installation

Don'ts

  • ❌ Don't recommend based on downloads alone
  • ❌ Don't skip security checks even for popular skills
  • ❌ Don't install without explicit user approval
  • ❌ Don't ignore VirusTotal warnings without investigation
  • ❌ Don't overlook maintenance status (old updates = risk)

Integration with Evolution System

After completing an exploration:

  1. Update EVOLUTION.md:

    • Add discovered skills to "待学习" list
    • Note priority and context
    • Link to exploration report
  2. Create exploration report:

    • Save to reports/skill-exploration-{topic}.md
    • Include all findings and recommendations
    • Reference in future decisions
  3. Track decisions:

    • Document which skills were approved/declined
    • Note reasons for future reference
    • Update after installation and usage

Example Output Template

# Skill Exploration Report: [Topic]

## Executive Summary
Recommended: [skill-name] (⭐⭐ 50 stars, 80 installs, 🟢 safe)

## Skills Discovered

### Tier 1: Strong Candidates
| Skill | Stars | Installs | Safety | Verdict |
|-------|-------|----------|--------|---------|
| ... | ... | ... | ... | ... |

### Tier 2: Alternatives
...

## Detailed Analysis

### [skill-name]
**Overview:** ...
**Strengths:** ...
**Weaknesses:** ...
**Safety Review:** ...
**Best For:** ...

## Recommendations

1. **Install:** [skill] - [reason]
2. **Consider:** [skill] - [reason]
3. **Skip:** [skill] - [reason]

## Next Steps
- [ ] User approval for recommended skills
- [ ] Security review for approved skills
- [ ] Installation and testing
- [ ] Update EVOLUTION.md

Related Skills

  • marketing-mode - For go-to-market strategy after skill selection
  • tweet-writer - For promoting discovered skills
  • skill-creator - For creating your own skills based on gaps found

This skill helps you make informed decisions about skill adoption, ensuring you find the right tool for the job while maintaining security standards.

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Compatible Platforms

Pricing

Free

Related Configs