database-optimizer
Optimizes database queries and improves performance across PostgreSQL and MySQL systems. Use when investigating slow queries, analyzing execution plans, or optimizing database performance. Invoke for index design, query rewrites, configuration tuning, partitioning strategies, lock contention resolution.
94
92%
Does it follow best practices?
Impact
Pending
No eval scenarios have been run
Passed
No known issues
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 its scope (database query optimization for PostgreSQL and MySQL), lists specific concrete actions, and provides explicit trigger guidance via both 'Use when' and 'Invoke for' clauses. The description uses proper third-person voice and includes a rich set of natural trigger terms that users would realistically use when seeking database performance help.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Lists multiple specific concrete actions: optimizing database queries, investigating slow queries, analyzing execution plans, index design, query rewrites, configuration tuning, partitioning strategies, and lock contention resolution. | 3 / 3 |
Completeness | Clearly answers both 'what' (optimizes database queries, improves performance across PostgreSQL and MySQL) and 'when' (explicit 'Use when' clause covering slow queries, execution plans, database performance, plus an 'Invoke for' clause listing specific scenarios). | 3 / 3 |
Trigger Term Quality | Includes strong natural keywords users would say: 'slow queries', 'execution plans', 'database performance', 'index design', 'query rewrites', 'configuration tuning', 'partitioning', 'lock contention', 'PostgreSQL', 'MySQL'. These cover a wide range of terms a user would naturally use when seeking database optimization help. | 3 / 3 |
Distinctiveness Conflict Risk | Clearly scoped to database query optimization for PostgreSQL and MySQL with distinct triggers like 'execution plans', 'index design', 'lock contention', and 'partitioning strategies' that are unlikely to conflict with non-database 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 well-structured, highly actionable skill with strong progressive disclosure and clear workflow sequencing including validation checkpoints. The executable SQL examples for both PostgreSQL and MySQL are copy-paste ready and the EXPLAIN patterns table is genuinely useful. Minor verbosity in the introductory sections and output templates prevents a perfect conciseness score, but overall this is a high-quality skill.
Suggestions
Remove the self-description opening line ('Senior database optimizer with expertise...') and the 'When to Use This Skill' section, as these duplicate the YAML frontmatter description and don't add actionable value.
Tighten the 'Output Templates' section — either provide a concrete example of a filled-out optimization report or remove it, as the current bullet list is generic enough that Claude would produce similar output without it.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Generally efficient but has some unnecessary framing (e.g., 'Senior database optimizer with expertise in...' self-description, the 'When to Use This Skill' section largely repeats what Claude would infer from context). The EXPLAIN output patterns table and SQL examples earn their place, but the output templates section at the end is somewhat generic. | 2 / 3 |
Actionability | Provides fully executable SQL queries for identifying slow queries, capturing execution plans, creating covering indexes, and validating improvements across both PostgreSQL and MySQL. The EXPLAIN output patterns table maps symptoms to concrete remedies, making guidance immediately actionable. | 3 / 3 |
Workflow Clarity | The core workflow is clearly sequenced with explicit validation checkpoints: capture baseline EXPLAIN ANALYZE first, implement changes incrementally, validate each change before proceeding, compare before/after metrics. The constraints section reinforces the feedback loop (never optimize without baseline, measure before and after every change, roll back if degradation occurs). | 3 / 3 |
Progressive Disclosure | Excellent structure with a concise overview in the main file and a clear reference table pointing to five topic-specific files with explicit 'Load When' guidance. References are one level deep and well-signaled. The main file contains enough actionable content to be useful standalone while deferring detailed guidance appropriately. | 3 / 3 |
Total | 11 / 12 Passed |
Validation
100%Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.
Validation — 11 / 11 Passed
Validation for skill structure
No warnings or errors.
- Repository
- jeffallan/claude-skills
- Commit
3d95bb1
- Reviewed
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