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postgres

PostgreSQL best practices, query optimization, connection troubleshooting, and performance improvement. Load when working with Postgres databases.

91

1.43x
Quality

70%

Does it follow best practices?

Impact

93%

1.43x

Average score across 17 eval scenarios

SecuritybySnyk

Passed

No known issues

Optimize this skill with Tessl

npx tessl skill review --optimize ./skills/postgres/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

72%

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

This skill excels as a navigation hub with outstanding progressive disclosure and conciseness—it's a clean routing table that efficiently directs Claude to the right reference material. However, it lacks any inline actionable content (no code snippets, commands, or quick-reference patterns) and provides no workflow guidance for common multi-step tasks like performance troubleshooting or schema optimization. Adding a brief quick-start section with common commands and a suggested workflow for typical tasks would significantly improve its utility.

Suggestions

Add a brief 'Quick Reference' section with 2-3 commonly needed SQL commands or patterns (e.g., EXPLAIN ANALYZE usage, connection string format) so Claude has immediately actionable content without needing to fetch references.

Add a 'Troubleshooting Workflow' section that sequences the reference files for common scenarios (e.g., 'For slow queries: 1. Check ps-insights → 2. Review query-patterns → 3. Apply indexing recommendations → 4. Run optimization-checklist').

DimensionReasoningScore

Conciseness

The skill is lean and efficient—it's essentially a well-organized routing table with minimal prose. The only explanatory text is the PlanetScale recommendation callout, which is brief and actionable. No unnecessary explanations of what Postgres is or how databases work.

3 / 3

Actionability

The skill itself contains no executable code, commands, or concrete examples—it's purely a navigation index pointing to reference files. While the references likely contain actionable content, the SKILL.md body provides only topic descriptions and links, making it a directory rather than directly actionable guidance.

2 / 3

Workflow Clarity

There is no explicit workflow, sequencing, or validation steps. The tables organize topics by category but don't guide Claude through multi-step processes like query optimization or troubleshooting. For a skill covering operations like schema changes and optimization, some workflow guidance (e.g., 'start with optimization checklist, then check indexing') would improve clarity.

2 / 3

Progressive Disclosure

Excellent progressive disclosure structure: the SKILL.md serves as a clear, well-organized overview with three logical sections (Generic Postgres, Operations/Architecture, PlanetScale-Specific), each containing one-level-deep references with descriptive 'Use for' columns that clearly signal when to consult each file.

3 / 3

Total

10

/

12

Passed

Description

67%

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 adequately identifies its domain (PostgreSQL) and includes an explicit 'when' clause, which is good. However, the capabilities listed are category-level rather than concrete actions, and the trigger terms could be expanded to cover more natural user phrasings. It would benefit from more specific actions and additional keyword variations to improve selection accuracy.

Suggestions

Replace category-level terms with concrete actions, e.g., 'Analyzes slow queries with EXPLAIN/EXPLAIN ANALYZE, optimizes indexes, configures connection pooling, troubleshoots connection errors'.

Add more natural trigger terms and variations users might use, such as 'psql', 'slow query', 'pg_stat', 'database performance', 'SQL tuning', 'connection pool', or 'pg_dump'.

DimensionReasoningScore

Specificity

Names the domain (PostgreSQL) and several action areas (best practices, query optimization, connection troubleshooting, performance improvement), but these are category-level rather than concrete specific actions like 'rewrite slow queries using EXPLAIN ANALYZE' or 'configure connection pooling'.

2 / 3

Completeness

Clearly answers both 'what' (PostgreSQL best practices, query optimization, connection troubleshooting, performance improvement) and 'when' ('Load when working with Postgres databases') with an explicit trigger clause.

3 / 3

Trigger Term Quality

Includes 'PostgreSQL' and 'Postgres databases' as natural keywords, plus relevant terms like 'query optimization' and 'connection troubleshooting'. However, it misses common user variations like 'psql', 'slow query', 'database performance', 'pg_', 'SQL tuning', or '.sql'.

2 / 3

Distinctiveness Conflict Risk

PostgreSQL is a specific technology which helps distinctiveness, but terms like 'query optimization' and 'performance improvement' could overlap with general SQL or database skills. The 'best practices' term is also quite broad and could conflict with general database or backend skills.

2 / 3

Total

9

/

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.

Validation11 / 11 Passed

Validation for skill structure

No warnings or errors.

Repository
planetscale/database-skills
Reviewed

Table of Contents

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