| name | skill-router-bzai |
| version | 1.0.0 |
| description | Cost-effective skill selector for maximizing ROI on AI operations (增收降本版 v1.0.0). Use when the user needs to accomplish a task and wants the optimal skill chosen automatically to minimize costs while maximizing quality. Evaluates skills based on quality (35%), token cost (30%), security/reliability (20%), and speed (15%). Searches both local skills and clawhub.com, presents top recommendations for user confirmation before execution. |
| metadata | {"purpose":"增收降本 - 智能选择最优技能以最小化Token成本"} |
Skill Router (增收降本版 v1.0.0)
智能技能选择器 - 用于增收降本的 AI 操作优化工具。
自动选择并执行最优技能，在保证质量的前提下最小化 Token 成本。
When to Use
- User wants to accomplish something but doesn't know which skill to use
- Multiple skills could solve the same problem - need to pick the best one
- Want to minimize token cost while maximizing quality
- Need to evaluate skills from clawhub.com before installation
Workflow
1. Parse Task
Analyze user request and decompose into atomic subtasks if needed.
2. Discover Skills
Search for candidate skills:
- List local installed skills:
openclaw skills list
- Search clawhub.com:
clawhub search <keywords>
3. Evaluate Candidates
For each candidate skill, score on:
| Dimension | Weight | Evaluation Criteria |
|---|
| Quality/Utility | 35% | User ratings, downloads, functionality match |
| Token Cost | 30% | Estimated input/output tokens based on skill complexity |
| Security/Reliability | 20% | Code audit, permissions, update frequency, author trust |
| Speed | 15% | API response time, execution efficiency |
Scoring Algorithm:
final_score = (quality × 0.35) + (token_score × 0.30) + (security × 0.20) + (speed × 0.15)
4. Generate Recommendations
Present Top-3 ranked options:
- Rank, skill name, final score
- Breakdown by dimension
- Estimated tokens and time
- Reasoning for recommendation
- Security assessment summary
5. User Confirmation
Wait for user to:
- Select option (1, 2, or 3)
- Request more details about a skill
- Cancel or modify the task
6. Execute
After confirmation:
- If skill not installed:
clawhub install <skill>
- Execute the skill with original user request
- Record actual metrics vs estimates
Security Assessment
Before recommending any skill from clawhub:
- Code Review: Check for suspicious patterns (network calls, file system access, credential harvesting)
- Permission Analysis: Verify requested permissions match functionality
- Author Verification: Prefer verified authors, established projects
- Update Frequency: Recently updated skills are preferred
- Community Trust: Ratings, issues, download count
Red flags that disqualify a skill:
- Requests excessive permissions for its stated purpose
- Contains obfuscated code
- Makes unexpected network calls
- Has no recent updates and low community engagement
Token Estimation
Estimate token costs based on:
- Skill description length/complexity
- Historical usage data (if available)
- Number of API calls required
- Output format verbosity
Store actual vs estimated for continuous improvement.
Scripts
scripts/evaluate_skill.py - Score a skill across all dimensionsscripts/search_clawhub.py - Search and fetch skill metadata from clawhubscripts/calculate_cost.py - Estimate token and time costs
References
references/evaluation-rubric.md - Detailed scoring criteriareferences/security-checklist.md - Security audit checklist
