self-assessment

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"