Skills Index

Skills are foundational knowledge modules that inform the design and implementation of agents, tools, and prompts.

Available Skills

LLM Evaluator

Path: skills/llm-evaluator/llm-evaluator.md

Covers LLM-as-a-Judge evaluation methodology including:

• Scoring approaches (direct, pairwise, reference-based)
• Evaluation metrics (classification, correlation)
• Known biases and mitigation strategies
• Implementation patterns

Key Takeaways:

• Use direct scoring for objective evaluations
• Use pairwise comparison for subjective preferences
• Always mitigate position bias
• Prefer classification metrics for interpretability

Context Fundamentals

Path: skills/context-fundamentals/context-fundamentals.md

Covers context engineering principles including:

• Context window management
• Information hierarchy
• Context types (static, dynamic, ephemeral)
• Relevance filtering

Key Takeaways:

• Structure context by priority
• Be explicit over implicit
• Remove redundancy
• Signal freshness of information

Tool Design

Path: skills/tool-design/tool-design.md

Covers agent tool design best practices including:

• Single responsibility principle
• Input/output schemas
• Error handling patterns
• AI SDK 6 features (approval, strict mode, examples)

Key Takeaways:

• Clear, validated schemas
• Predictable output structure
• Graceful error handling
• Consider approval for dangerous tools

Skill Application Matrix

Adding New Skills

1. Create skill directory: skills/<skill-name>/
2. Create main file: skills/<skill-name>/<skill-name>.md
3. Include:

• Overview and purpose
• Core principles
• Practical patterns
• Implementation examples
• References

1. Update this index

Skill Development Guidelines

• Focus on principles that transfer across implementations
• Include concrete examples and patterns
• Reference authoritative sources
• Keep content actionable, not just theoretical
• Update as understanding evolves