analyzing-database-indexes
Process use when you need to work with database indexing. This skill provides index design and optimization with comprehensive guidance and automation. Trigger with phrases like "create indexes", "optimize indexes", or "improve query performance".
77
73%
Does it follow best practices?
Impact
Pending
No eval scenarios have been run
Passed
No known issues
Optimize this skill with Tessl
npx tessl skill review --optimize ./plugins/database/database-index-advisor/skills/analyzing-database-indexes/SKILL.mdQuality
Discovery
82%Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.
The description covers the basics with explicit trigger phrases and a clear 'when to use' clause, which is its strongest aspect. However, the 'what it does' portion is weak—'comprehensive guidance and automation' is vague filler, and the opening 'Process use when' is awkward phrasing. The description would benefit from listing more specific concrete actions it can perform.
Suggestions
Replace 'comprehensive guidance and automation' with specific concrete actions like 'analyze query execution plans, recommend composite indexes, identify redundant or unused indexes, generate CREATE INDEX statements'.
Fix the awkward opening 'Process use when you need to work with database indexing' to a clearer third-person statement like 'Designs and optimizes database indexes to improve query performance'.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Names the domain (database indexing) and mentions 'index design and optimization' but lacks specific concrete actions beyond that. 'Comprehensive guidance and automation' is vague filler rather than listing specific capabilities like 'analyze query plans, suggest composite indexes, detect unused indexes'. | 2 / 3 |
Completeness | Explicitly answers both 'what' (index design and optimization) and 'when' (trigger phrases like 'create indexes', 'optimize indexes', 'improve query performance'). The trigger guidance is explicit with example phrases. | 3 / 3 |
Trigger Term Quality | Includes natural trigger phrases users would say: 'create indexes', 'optimize indexes', 'improve query performance'. These are realistic terms a user would use when needing this skill, covering both creation and optimization scenarios. | 3 / 3 |
Distinctiveness Conflict Risk | Database indexing is a reasonably specific niche, but 'improve query performance' could overlap with query optimization skills that don't involve indexing. The description could be more precise about what distinguishes it from general database performance tuning. | 2 / 3 |
Total | 10 / 12 Passed |
Implementation
64%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This is a solid, highly actionable skill with executable SQL queries and concrete examples throughout. Its main weaknesses are moderate verbosity (explaining concepts Claude already understands about database internals) and missing explicit validation/feedback loops after index creation steps. The content would benefit from tighter prose and a verify-after-action checkpoint.
Suggestions
Add an explicit validation step after index creation (e.g., 'Run EXPLAIN ANALYZE on the original query to confirm the new index is used and measure improvement') to close the feedback loop.
Trim explanatory text that Claude already knows, such as what sequential scans are, what n_distinct means, or how B-tree indexes work with correlation values—keep only the decision rules.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The content is mostly efficient with actionable SQL queries and concrete guidance, but includes some unnecessary elaboration (e.g., explaining what sequential scans mean, what correlation values indicate) that Claude already knows. The examples section, while useful, is somewhat verbose with narrative descriptions. | 2 / 3 |
Actionability | Provides fully executable SQL queries for every analysis step, concrete CREATE INDEX and DROP INDEX statements, specific EXPLAIN syntax, and real-world examples with measurable outcomes. The guidance is copy-paste ready throughout. | 3 / 3 |
Workflow Clarity | Steps are clearly sequenced from identification through analysis to recommendation, but lacks explicit validation checkpoints and feedback loops. For example, after creating an index there's no 'verify the index is being used' step, and there's no explicit loop for re-running EXPLAIN after index creation to confirm improvement. | 2 / 3 |
Progressive Disclosure | The content is well-structured with clear sections (Instructions, Output, Error Handling, Examples, Resources), but it's a monolithic document that could benefit from splitting detailed PostgreSQL vs MySQL guidance into separate files. The Resources section provides external links but no internal file references for advanced topics. | 2 / 3 |
Total | 9 / 12 Passed |
Validation
81%Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.
Validation — 9 / 11 Passed
Validation for skill structure
| Criteria | Description | Result |
|---|---|---|
allowed_tools_field | 'allowed-tools' contains unusual tool name(s) | Warning |
frontmatter_unknown_keys | Unknown frontmatter key(s) found; consider removing or moving to metadata | Warning |
Total | 9 / 11 Passed | |
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