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postgresql-optimization

PostgreSQL database optimization workflow for query tuning, indexing strategies, performance analysis, and production database management.

Quality

59%

Does it follow best practices?

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SecuritybySnyk

Passed

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tessl review fix ./plugins/AI-Agents-Safe-Coding-Skills-claude/skills/postgresql-optimization/SKILL.md

The canonical home for this skill is postgresql-optimization in administrakt0r/AI-Agents-Safe-Coding-Skills

SKILL.md
Quality
Evals
Security

Quality

Content

38%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.

The skill has a clear seven-phase structure but delivers almost entirely generic, high-level directives with no executable detail — no example SQL, configuration values, or validation loops — plus redundant checklists and copy-paste prompts that add tokens without information. It is a well-organized skeleton that needs concrete, database-specific content and validation checkpoints to be actionable.

Suggestions

Add executable detail to each phase: example EXPLAIN ANALYZE output interpretation, pg_stat_statements queries for finding slow queries, concrete starting values for shared_buffers/work_mem/effective_cache_size, and example CREATE INDEX statements.

Introduce validation checkpoints and feedback loops, e.g. capture query timings before changes, re-run EXPLAIN ANALYZE after, and only proceed when improvement is verified.

Remove redundancy: merge the near-duplicate "Optimization Checklist" and "Quality Gates" sections and drop the "Copy-Paste Prompts" blocks that merely restate each phase title.

DimensionReasoningScore

Conciseness

The body is noticeably padded: two nearly redundant checklists ("Optimization Checklist" and "Quality Gates") repeat the phase outcomes, "Copy-Paste Prompts" merely restate each phase title, and the actions are generic steps Claude already knows ("Check database version", "Review configuration", "Review trends"). This matches the anchor for several unnecessary or padded sections rather than the mostly-efficient level 3.

2 / 5

Actionability

Almost all guidance is high-level hints ("Identify scan types", "Check join strategies", "Find optimization opportunities", "Review index usage") with no SQL examples, no configuration values, no scripts, and no concrete commands beyond naming EXPLAIN ANALYZE and VACUUM. The specific steps to execute are missing, matching the minimal-concrete-guidance anchor rather than level 3's "some concrete guidance but incomplete".

2 / 5

Workflow Clarity

The seven phases are clearly sequenced and steps are listed, but there are no explicit validation checkpoints or feedback loops (e.g., measure before/after with EXPLAIN ANALYZE timings, verify index usage with pg_stat_user_indexes). The scoring notes cap database-operation workflows without validation at 3, which fits the "sequence present but checkpoints missing or implicit" anchor.

3 / 5

Progressive Disclosure

No bundle files exist (references/, scripts/, assets/ are absent) and the body is well-organized with consistent per-phase headers, checklists, and a related-workflows section, making it easy to navigate. It is not a 5 because the content exceeds 50 lines with repeated scaffolding that could be consolidated or split, leaving minor organization gaps rather than fully appropriate placement.

4 / 5

Total

11

/

20

Passed

Description

61%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 clear, domain-specific description with good natural keywords, but it omits any "Use when..." trigger clause, capping completeness at 3. Adding explicit usage triggers and the common synonym "Postgres" would raise it substantially.

Suggestions

Append an explicit trigger clause, e.g. "Use when the user mentions PostgreSQL, Postgres, slow queries, indexing, or database performance tuning."

Include the common synonym "Postgres" and natural phrases like "slow queries" or "optimize my database" among the trigger terms.

Replace the generic "production database management" with more concrete actions such as "tune server configuration and schedule VACUUM/ANALYZE maintenance".

DimensionReasoningScore

Specificity

The description names the domain (PostgreSQL database optimization) and capability areas like "query tuning" and "indexing strategies", but these are activity categories rather than concrete actions, and "production database management" is generic — matching the anchor for a clear domain with 1-2 concrete actions but not comprehensive coverage. Not a 4 because it lacks the specific, verifiable actions of the level-4 example ("extracts text, fills forms, converts pages").

3 / 5

Completeness

The "what" is clear ("optimization workflow for query tuning, indexing strategies, performance analysis, and production database management"), but there is no "Use when..." clause or equivalent explicit trigger guidance anywhere in the description. Per the judging guidelines, a missing 'Use when...' clause caps completeness at 3, which is the best fit.

3 / 5

Trigger Term Quality

Good keyword coverage: "PostgreSQL", "query tuning", "indexing", "performance analysis", "database" are all terms users would naturally say. A few natural terms are missing — notably the extremely common synonym "Postgres", as well as "slow queries" and file extensions like ".sql" — so it does not reach the comprehensive level 5.

4 / 5

Distinctiveness Conflict Risk

"PostgreSQL" establishes a clear, specific niche that distinguishes it from generic skills, with only minor overlap risk against broad database-administration or SQL-performance skills. It is not a 5 because the level-5 anchor expects distinct trigger phrases, and phrases like "performance analysis" and "production database management" could also match more general database skills.

4 / 5

Total

14

/

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

frontmatter_unknown_keys

Unknown frontmatter key(s) found; consider removing or moving to metadata

Warning

Total

15

/

16

Passed

Repository

administrakt0r/AI-Agents-Safe-Coding-Skills

Path

plugins/AI-Agents-Safe-Coding-Skills-claude/skills/postgresql-optimization/SKILL.md

Reviewed

Table of Contents

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