Name: postgresql-optimization
Rating: 53.6 (1 reviews)
Author: administrakt0r

postgresql-optimization

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

Quality

60%

Does it follow best practices?

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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

Quality

Content

61%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 workflow is well-structured into sequenced phases with named skills and prompts, but it lacks executable SQL/command detail and per-phase validation checkpoints for what are inherently destructive production database operations.

Suggestions

Add per-phase validation steps and feedback loops (e.g. after adding an index, re-run EXPLAIN ANALYZE to confirm improvement before proceeding) to lift workflow clarity above the destructive-operation cap.

Include concrete, copy-paste-ready SQL or commands for key actions (e.g. sample CREATE INDEX statements, EXPLAIN ANALYZE snippets, recommended shared_buffers/work_mem starting values) to improve actionability.

Merge the redundant "Optimization Checklist" and "Quality Gates" sections into a single checklist to remove the main conciseness bloat.

Dimension	Reasoning	Score
Conciseness	The body is lean and list-based with no padding explaining concepts Claude already knows; the only bloat is the near-duplicate "Optimization Checklist" and "Quality Gates" sections, which keeps it just below a 5.	4 / 5
Actionability	It provides named skills to invoke and copy-paste prompts, plus concrete action verbs ("Run EXPLAIN ANALYZE", "Create B-tree indexes", "Tune shared_buffers"), but no actual SQL snippets or commands, so the guidance stays at a high level rather than being fully executable.	3 / 5
Workflow Clarity	Seven phases are clearly sequenced, but production database operations (VACUUM, config tuning, indexing on a live DB) are destructive/batch in nature and the phases lack per-step validation checkpoints or feedback loops, which caps workflow clarity at 3 per the rubric.	3 / 5
Progressive Disclosure	Content is well-organized into clearly headed phases and checklists with no bundle files present and no nested references; it is not a 5 only because some phase detail (e.g. indexing strategy, config values) could arguably live in separate reference files.	4 / 5
	Total	14 / 20 Passed

Description

58%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.

The description clearly states what the skill does and is PostgreSQL-specific, but it omits any explicit "when to use" trigger guidance and lacks natural synonym keywords, which limit its completeness and trigger-term quality.

Suggestions

Add an explicit "Use when..." clause with concrete triggers, e.g. "Use when optimizing slow PostgreSQL queries, designing indexes, or tuning production database configuration."

Include natural user phrasings and synonyms such as "slow queries", "Postgres", and ".sql" to improve trigger-term coverage.

Split the bundled capabilities into more discrete concrete actions (e.g. "run EXPLAIN ANALYZE", "create B-tree and partial indexes") to push specificity toward comprehensive coverage.

Dimension	Reasoning	Score
Specificity	Names the domain and lists several concrete capabilities ("query tuning, indexing strategies, performance analysis, and production database management"); not a 5 because the actions are stated at a category level rather than as multiple distinct concrete operations.	4 / 5
Completeness	The "what" is clearly stated (optimization workflow for query tuning, indexing, etc.) but there is no "Use when..." clause or equivalent explicit trigger guidance, which caps completeness at 3 per the rubric.	3 / 5
Trigger Term Quality	Relevant terms like "PostgreSQL", "query tuning", "indexing", and "performance analysis" appear, but common natural variations users would say ("slow queries", "Postgres", ".sql") are missing.	3 / 5
Distinctiveness Conflict Risk	The PostgreSQL-specific niche ("PostgreSQL database optimization workflow") is mostly distinct with only minor overlap risk against general database skills; not a 5 because it could still overlap with generic database-administration skills.	4 / 5
	Total	14 / 20 Passed

Validation

93%

Warnings & errors only

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

Criteria	Description	Result
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
Commit: 57c135b

Reviewed: 3 days ago

Table of Contents

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