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postgres-best-practices

Postgres performance optimization and best practices. Use when writing or reviewing SQL queries, designing schemas, configuring connection pooling, fixing N+1 queries, creating indexes, implementing row-level security, diagnosing slow queries with EXPLAIN ANALYZE, or optimizing database performance. Postgres only — for DynamoDB use aws-dynamodb-best-practices; does not cover ORM- or migration-tool-specific APIs.

72

Quality

90%

Does it follow best practices?

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SecuritybySnyk

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SKILL.md
Quality
Evals
Security

Quality

Content

86%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

Excellent progressive disclosure: the body is a lean, well-organized index over 31 verified reference files, with a priority table and an explicit navigation procedure. The two weaker spots are that no executable SQL appears in the body itself (it is fully delegated to reference files) and the workflow lacks any validation or verification guidance for applying the rules.

Suggestions

Include one or two key inline snippets for the CRITICAL categories (e.g., the canonical EXPLAIN ANALYZE invocation or a covering-index example) in SKILL.md so the highest-impact guidance is immediately actionable without a file hop.

Add brief symptom-to-category mapping (e.g., 'slow query → start with query-*', 'too many connections → conn-*') so users' problems route to the right rules faster than the category-priority table alone.

Add a short validation step in 'How to Use' (e.g., re-run EXPLAIN ANALYZE before/after applying an index or schema change) since the rules target database operations where verifying the fix matters.

DimensionReasoningScore

Conciseness

The body is a lean index: no explanations of concepts Claude already knows, no padded prose; every element earns its place — the one-line rule directives, and the priority table which adds impact/prefix data beyond the section headers. This matches anchor 5 ('lean and efficient; every token earns its place') better than anchor 4, since the table/category-header overlap is structural navigation, not over-explanation.

5 / 5

Actionability

Concrete directives ('Use cursor-based pagination instead of OFFSET', 'Add indexes on WHERE and JOIN columns') and a concrete command ('Glob the prefix (for example references/query-*.md)') give mostly actionable guidance, but all executable SQL lives one hop away in the reference files, leaving the minor gap that anchor 4 describes ('concrete code or commands with minor gaps') rather than anchor 5's copy-paste-ready code.

4 / 5

Workflow Clarity

The lookup workflow is an unambiguous sequence ('Read individual files as needed; to review a whole category, Glob the prefix, then Read the files in one turn') and the priority table guides category selection, but there are no validation checkpoints or error-recovery guidance — anchor 4 ('clear sequence with most checkpoints present; minor validation gaps') fits better than anchor 5, which demands explicit validation steps and feedback loops.

4 / 5

Progressive Disclosure

A clear overview with well-signaled one-level-deep references: all 31 rule files listed in the quick reference were verified to exist in references/ with matching prefixes, and the 'How to Use' section explicitly describes each file's contents ('explanation, incorrect/correct SQL examples, EXPLAIN output, and context') plus a concrete Glob navigation pattern — matching anchor 5.

5 / 5

Total

18

/

20

Passed

Description

92%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

A strong description: concrete action enumeration, an explicit 'Use when...' trigger clause, and proactive boundary/disambiguation guidance (DynamoDB redirection, ORM/migration exclusions). The only gap is missing common synonyms such as 'PostgreSQL' and file extensions like '.sql', which keeps trigger-term coverage just short of comprehensive.

DimensionReasoningScore

Specificity

Lists 7+ concrete, domain-specific actions ('fixing N+1 queries', 'implementing row-level security', 'diagnosing slow queries with EXPLAIN ANALYZE', 'configuring connection pooling') with comprehensive coverage of the Postgres performance domain, matching the anchor-5 example of multiple specific concrete actions; anchor 4's 'minor gaps' does not apply.

5 / 5

Completeness

Explicitly answers 'what' ('Postgres performance optimization and best practices' plus an enumerated action list) and 'when' ('Use when writing or reviewing SQL queries, designing schemas, configuring connection pooling...') with concrete trigger phrases, exactly matching anchor 5; anchor 4's 'when could be more explicit' is too weak for this level of trigger specificity.

5 / 5

Trigger Term Quality

Good keyword coverage with natural phrases users say ('SQL queries', 'N+1 queries', 'indexes', 'row-level security', 'slow queries', 'EXPLAIN ANALYZE'), but common synonyms and extensions like 'PostgreSQL' and '.sql' are missing, placing it at anchor 4 ('a few natural terms missing') rather than 5.

4 / 5

Distinctiveness Conflict Risk

Clear niche with explicit boundaries and conflict prevention ('Postgres only — for DynamoDB use aws-dynamodb-best-practices; does not cover ORM- or migration-tool-specific APIs'), giving minimal conflict risk as anchor 5 requires.

5 / 5

Total

19

/

20

Passed

Validation

93%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

referenced_paths_exist

Referenced path issues: 1 missing

Warning

Total

15

/

16

Passed

Repository

provectus/awos-recruitment

Path

registry/skills/postgres-best-practices/SKILL.md

Reviewed

Table of Contents

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