g14wxz/db-diagnostics-inspection
Provides database health diagnostics via slow query analysis, bottleneck identification, and Postgres inspection.
100
100%
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 follows best practices closely. It uses third-person voice, lists specific concrete actions, includes a comprehensive 'Use when...' clause with natural trigger terms, and targets a clear niche (Postgres/Supabase database health diagnostics). It closely mirrors the good examples provided in the rubric.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Lists multiple specific concrete actions: 'analyzing slow queries', 'identifying bottlenecks', and 'checking Postgres performance indicators'. These are clear, actionable capabilities. | 3 / 3 |
Completeness | Clearly answers both 'what' (inspects database health by analyzing slow queries, identifying bottlenecks, checking Postgres performance indicators) and 'when' with an explicit 'Use when...' clause listing five distinct trigger scenarios. | 3 / 3 |
Trigger Term Quality | Excellent coverage of natural terms users would say: 'slow queries', 'database issues', 'DB health', 'performance bottlenecks', 'Supabase Postgres', 'troubleshooting'. These are terms users would naturally use when experiencing database problems. | 3 / 3 |
Distinctiveness Conflict Risk | Highly distinctive with a clear niche: Postgres/Supabase database health and performance diagnostics. The combination of 'Supabase Postgres', 'slow queries', and 'performance indicators' creates a well-defined scope unlikely to conflict with other skills. | 3 / 3 |
Total | 12 / 12 Passed |
Implementation
100%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This is an excellent skill that provides a complete, actionable database health inspection workflow. It excels at conciseness by providing exact SQL queries and specific thresholds without explaining basic concepts. The four-phase structure with pre-conditions, cross-referencing between phases, HALT conditions, and a structured output report demonstrates strong workflow design.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Every line serves a purpose — specific SQL queries, concrete thresholds, and clear flags. No unnecessary explanation of what Postgres is or how databases work. Assumes Claude's competence throughout. | 3 / 3 |
Actionability | Provides fully executable SQL queries ready to copy-paste via MCP execute_sql, with specific numeric thresholds (mean_exec_time > 100ms, seq_scan > 1000, n_dead_tup > 10000, 80% of max_connections) for decision-making. Nothing is left vague. | 3 / 3 |
Workflow Clarity | Four clearly sequenced phases with explicit pre-conditions, cross-referencing between phases (Phase 3 references Phase 2 findings), HALT conditions for missing extensions and CRITICAL findings, and a structured verification report with severity ratings serving as the validation checkpoint. | 3 / 3 |
Progressive Disclosure | For a skill of this scope (~50 lines, single diagnostic workflow), the content is well-organized into logical phases with clear section headers. No need for external file references given the focused nature of the task, and the structure supports easy scanning. | 3 / 3 |
Total | 12 / 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.
Reviewed
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