| name | self-assessment |
| description | Skills evaluate their own performance, capabilities, and limitations. Honest self-reflection drives improvement. Use when working with self assessment. |
| domain | meta |
| author | oyi77 |
| license | Apache-2.0 |
| subdomain | meta-skills |
| tags | ["assessment","meta-learning","self","self-improvement","skill-evolution"] |
| persona | {"name":"Honest Self-Evaluator","expertise":"Introspection, capability analysis, gap identification","philosophy":"Know thyself"} |
| version | 1.0.0 |
Self Assessment
When to Use
Trigger phrases:
- "self assessment"
- "Help me with self assessment"
Use cases:
- When the task matches this skill's domain expertise
When NOT to use:
- For tasks outside this skill's scope
/self-assessment run skill-name
View assessment history
/self-assessment history skill-name
Compare to peer skills
/self-assessment benchmark skill-name --category marketing
### Reflection Questions
1. What did I do well?
2. Where did I struggle?
3. What patterns do I see in my failures?
4. How do I compare to similar skills?
5. What should I learn next?
### Output
```yaml
assessment_report:
skill: seo-optimizer
timestamp: 2026-05-04
overall_score: 0.79
strengths:
- comprehensive analysis
- good error handling
weaknesses:
- slow on large sites
- limited JavaScript support
recommendations:
- optimize for speed
- add headless browser support
When NOT to Use
- When the skill is stable and not changing
- For skills with fewer than 10 invocations (not enough data)
- When manual curation produces better results
Overview
Self Assessment is a foundational meta-skills skill that provides skill management capabilities for the agent ecosystem.
Architecture
- Input layer — Receives and validates incoming requests
- Processing layer — Core logic for skill management
- Output layer — Formats and delivers results
- State management — Maintains context across invocations
Configuration
- Set up required environment variables and paths
- Configure logging level and output format
- Define resource limits (memory, time, API calls)
- Enable/disable features via configuration flags
Integration
- Exposes standard interfaces for other skills to consume
- Supports event-driven and request-response patterns
- Compatible with the 1ai-skills hook system
- Logs metrics for the skill performance monitor
Anti-Rationalization Table
| Rationalization | Reality |
|---|
| "Skills do not need to evolve" |
