Name: database-optimizer
Rating: 42.4 (1 reviews)
Author: administrakt0r

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database-optimizer

Expert database optimizer specializing in modern performance tuning, query optimization, and scalable architectures.

Quality

42%

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tessl review fix ./plugins/AI-Agents-Safe-Coding-Skills/skills/database-optimizer/SKILL.md

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

Quality

Content

35%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 body is an exhaustive but verbose capability catalog with little executable guidance and no real bundle files. Its workflow sequence exists but lacks concrete validation, and its single reference is broken and buried.

Suggestions

Cut the 13 capability/behavioral/knowledge catalog sections down to a lean overview and move the detail into reference files under references/ (which currently do not exist).

Add executable examples (e.g., an EXPLAIN ANALYZE walkthrough, a CREATE INDEX CONCURRENTLY snippet, a pgbench command) instead of only listing concepts.

Fix the broken reference path ('resources/implementation-playbook.md' → 'references/implementation-playbook.md') and create the referenced file, or remove the pointer.

Add explicit validation checkpoints with concrete commands to the Response Approach (e.g., 'Re-run pgbench; confirm p99 latency dropped; if regression, revert index').

Dimension	Reasoning	Score
Conciseness	The ~155-line body is a padded catalog of concepts Claude already knows (B-tree/GiST/GIN/BRIN indexes, EXPLAIN ANALYZE, N+1 patterns, Redis caching) spread across 13 capability subsections, making it noticeably verbose with several padded sections.	2 / 5
Actionability	Guidance is almost entirely high-level: generic 'Instructions' and a 9-step 'Response Approach' with no executable code, commands, or copy-paste snippets, though specific tool names like pg_stat_statements and pgbench appear in passing.	2 / 5
Workflow Clarity	A coherent 9-step 'Response Approach' sequence is present, but validation checkpoints are abstract ('Validate improvements through comprehensive benchmarking') with no concrete validation command or error-recovery feedback loop; the destructive/batch database operations (migrations, schema changes) cap this at 3.	3 / 5
Progressive Disclosure	There is genuine section structure (13 named subsections) and a reference to a playbook, but the reference is misspelled ('resources/' vs 'references/'), the file does not exist, and the bulk capability detail that should live in separate files is inlined, so it is only moderately well organized.	3 / 5
	Total	10 / 20 Passed

Description

50%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 conveys the database-optimization domain and specializations but lacks an explicit 'when to use' trigger clause and uses fairly broad optimization language. Trigger-term coverage and distinctiveness are middling rather than strong.

Suggestions

Add an explicit 'Use when...' clause naming concrete triggers like 'slow queries', 'missing indexes', or 'database migration planning'.

Replace broad phrasing ('modern performance tuning') with concrete actions users would say, e.g. 'analyze EXPLAIN plans, design indexes, resolve N+1 queries'.

Include common synonyms/file cues (SQL, PostgreSQL/MySQL, slow query logs) to improve trigger-term coverage and reduce overlap with generic performance skills.

Dimension	Reasoning	Score
Specificity	Names the domain ('database optimizer') and a couple of concrete specialization areas ('performance tuning, query optimization, scalable architectures'), but these are areas rather than a list of several specific concrete actions, so it is not comprehensive enough for a 4.	3 / 5
Completeness	The 'what' is clearly stated, but there is no 'Use when...' clause or equivalent trigger guidance in the description field, which the rubric caps at 3.	3 / 5
Trigger Term Quality	Relevant natural phrases like 'database', 'performance tuning', and 'query optimization' appear, but common user variations/synonyms such as 'slow queries', 'indexes', and 'SQL' are missing, so coverage is partial rather than good.	3 / 5
Distinctiveness Conflict Risk	The database-performance niche is somewhat specific, but the broad optimization language ('performance tuning', 'optimization') leaves overlap risk with general performance/development skills, so it is not mostly-distinct enough for a 4.	3 / 5
	Total	12 / 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/skills/database-optimizer/SKILL.md
Commit: 57c135b

Reviewed: 3 days ago

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