recommendation-system
Deploy production recommendation systems with feature stores, caching, A/B testing. Use for personalization APIs, low latency serving, or encountering cache invalidation, experiment tracking, quality monitoring issues.
92
92%
Does it follow best practices?
Impact
92%
1.21xAverage score across 3 eval scenarios
Advisory
Suggest reviewing before use
Quality
Discovery
100%Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.
This is a strong skill description that clearly defines a specific technical domain (production recommendation systems) with concrete capabilities and explicit trigger conditions. It uses third person voice correctly and includes a comprehensive set of natural keywords that users would actually use when needing this skill. The 'Use for...' clause effectively communicates when Claude should select this skill.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Lists multiple specific concrete actions: 'Deploy production recommendation systems with feature stores, caching, A/B testing' clearly names the domain and specific technical components involved. | 3 / 3 |
Completeness | Clearly answers both what ('Deploy production recommendation systems with feature stores, caching, A/B testing') and when ('Use for personalization APIs, low latency serving, or encountering cache invalidation, experiment tracking, quality monitoring issues'). | 3 / 3 |
Trigger Term Quality | Includes strong natural keywords users would say: 'recommendation systems', 'feature stores', 'caching', 'A/B testing', 'personalization APIs', 'low latency serving', 'cache invalidation', 'experiment tracking', 'quality monitoring'. | 3 / 3 |
Distinctiveness Conflict Risk | Highly specific niche combining recommendation systems with production deployment concerns (feature stores, A/B testing, cache invalidation). Unlikely to conflict with general ML skills or generic deployment skills. | 3 / 3 |
Total | 12 / 12 Passed |
Implementation
85%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This is a strong, production-focused skill with excellent actionability and clear workflows. The code examples are executable and address real-world concerns like cache invalidation, cold start, and A/B testing. Minor verbosity in the 'When to Use' section and some pattern repetition prevent a perfect conciseness score, but overall this skill provides substantial value for building recommendation systems.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The skill is reasonably efficient but includes some redundancy - the 'When to Use This Skill' section largely duplicates the description, and some patterns (like RecommendationService) repeat concepts already shown. The architecture diagram and tables add value, but the overall length (~400 lines) could be tightened. | 2 / 3 |
Actionability | Excellent executable code throughout - the Quick Start provides copy-paste ready bash commands and Python code, all code examples are complete and runnable, and specific libraries with version numbers are provided. The Known Issues section provides concrete solutions with working code. | 3 / 3 |
Workflow Clarity | The Quick Start has clear numbered steps (1-5) with explicit commands. The RecommendationService pattern shows a clear 5-step workflow with comments. Cache invalidation and validation patterns are explicit with clear triggers and feedback loops for error handling. | 3 / 3 |
Progressive Disclosure | Well-structured with Quick Start for immediate use, then deeper sections for architecture, components, and known issues. The 'When to Load References' section clearly signals one-level-deep references to detailed implementation files with specific use cases for each. | 3 / 3 |
Total | 11 / 12 Passed |
Validation
90%Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.
Validation — 10 / 11 Passed
Validation for skill structure
| Criteria | Description | Result |
|---|---|---|
frontmatter_unknown_keys | Unknown frontmatter key(s) found; consider removing or moving to metadata | Warning |
Total | 10 / 11 Passed | |
- Repository
- secondsky/claude-skills
- Commit
90d6bd7
- Reviewed
Table of Contents
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