Name: database-optimizer
Rating: 40 (1 reviews)
Author: administrakt0r

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database-optimizer

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

Quality

38%

Does it follow best practices?

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

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

Quality

Content

23%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 a verbose buzzword catalogue of database topics Claude already knows, with no executable code or concrete commands and a dangling reference to a non-existent playbook; the response workflow is sequenced but lacks concrete validation checkpoints.

Suggestions

Replace the capability enumeration with actionable guidance: concrete EXPLAIN/INDEX/caching recipes with executable SQL or shell examples for the most common optimization cases.

Trim the 'Capabilities', 'Knowledge Base', and 'Behavioral Traits' sections, which restate knowledge Claude already has, and keep only non-obvious decision rules or heuristics.

Add a concrete validate->fix->retry loop for risky database operations (e.g. 'run EXPLAIN ANALYZE before/after, compare timings, revert index if regression') and either create the referenced implementation-playbook.md or remove the dangling reference.

Dimension	Reasoning	Score
Conciseness	The body is a long, padded catalogue of database capabilities and tool names (EXPLAIN ANALYZE, pg_stat_statements, B-tree/GiST/GIN, etc.) that Claude already knows, with no novel procedural knowledge; not a 1 because it does not explain elementary concepts, but it is noticeably verbose with many unnecessary padded sections.	2 / 5
Actionability	There is no executable code, no concrete commands, and no copy-paste examples — only abstract descriptions ('Apply relevant best practices and validate outcomes', 'Execution plan analysis: EXPLAIN ANALYZE'); the single referenced playbook does not exist, so the skill describes rather than instructs.	1 / 5
Workflow Clarity	The 9-step 'Response Approach' provides a sequence (analyze, identify, design, implement, monitor, validate) but validation checkpoints are implicit and generic, and per the rubric's database-operation feedback-loop cap, missing concrete validate/fix/retry loops caps this at 3.	3 / 5
Progressive Disclosure	The entire capabilities catalogue is inlined in SKILL.md rather than split into reference files, and the only reference ('resources/implementation-playbook.md') is buried in a bullet and does not resolve to an existing file; structure exists via headers but content that belongs in separate files is inlined.	2 / 5
	Total	8 / 20 Passed

Description

53%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 identifies the database-optimization niche and a few activity areas, but it omits any explicit 'Use when...' trigger guidance and relies on generic capability labels rather than concrete actions, capping completeness and trigger-term quality.

Suggestions

Add an explicit 'Use when...' clause naming concrete trigger phrases users would say (e.g. 'Use when tuning slow queries, optimizing SQL, designing indexes, or scaling database workloads').

Replace abstract capability labels with a few concrete actions (e.g. 'analyze EXPLAIN plans, design composite indexes, resolve N+1 queries, plan sharding strategies').

Include common synonyms and file/technology triggers (e.g. 'slow queries', 'SQL', 'PostgreSQL', 'index tuning') to broaden natural keyword coverage.

Dimension	Reasoning	Score
Specificity	Names the domain ('Expert database optimizer') and a couple of activity areas ('performance tuning', 'query optimization', 'scalable architectures'), but these are generic capability areas rather than concrete actions like 'extract text' or 'fill forms'; not a 2 because two-plus activities are named, not a 4 because the actions are abstract rather than specific.	3 / 5
Completeness	There is a clear 'what' (expert database optimizer specializing in performance tuning, query optimization, scalable architectures) but no explicit 'Use when...' trigger clause, and per the judging guideline a missing 'Use when...' clause caps completeness at 3.	3 / 5
Trigger Term Quality	Terms like 'database optimizer', 'performance tuning', and 'query optimization' are terms users might say, but common variations/synonyms (slow queries, indexing, SQL tuning) are missing; not a 4 because keyword coverage is narrow and lacks synonyms.	3 / 5
Distinctiveness Conflict Risk	Database performance optimization is a fairly clear niche with distinct triggers and only minor overlap risk with closely related dev/dba skills; not a 5 because the lack of concrete triggers leaves some ambiguity versus a general coding skill.	4 / 5
	Total	13 / 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/database-optimizer/SKILL.md
Commit: 57c135b

Reviewed: 3 days ago

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