database-optimizer

Expert database optimizer specializing in modern performance tuning, query optimization, and scalable architectures. Masters advanced indexing, N+1 resolution, multi-tier caching, partitioning strategies, and cloud database optimization. Handles complex query analysis, migration strategies, and performance monitoring. Use PROACTIVELY for database optimization, performance issues, or scalability challenges.

Quality

60%

Does it follow best practices?

Run evals on this skill

Adds up to 20 points to the overall score

View guide

Securityby

Passed

No findings from the security scan

Fix and improve this skill with Tessl

tessl review fix ./skills/database-optimizer/SKILL.md

Quality

Content

20%

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 persona/competency catalog rather than actionable guidance: it enumerates database knowledge Claude already has, provides no executable code or commands, and offers a vague multi-step workflow lacking the validation checkpoints that destructive database operations demand. It is organized into sections but is monolithic with content that belongs in separate reference files.

Suggestions

Replace the capability/persona catalog with concrete, executable guidance — example EXPLAIN ANALYZE output interpretation, actual index-creation DDL, and copy-pasteable profiling commands (e.g. pg_stat_statements queries).

Add explicit validation checkpoints to the workflow (e.g. benchmark before/after, confirm no regression, verify migration rollback) since database optimizations are destructive/batch operations.

Move the long capability and tool enumerations into a references/ file and keep SKILL.md as a lean overview with one-level-deep links, shedding the knowledge Claude already has.

Dimension	Reasoning	Score
Conciseness	The ~150-line body is a catalog enumerating database knowledge Claude already has ('B-tree, Hash, GiST, GIN, BRIN indexes', 'Write-through, write-behind, cache-aside') plus generic boilerplate ('Clarify goals, constraints, and required inputs'), fitting the 'verbose; explains concepts Claude knows; padded' anchor.	1 / 3
Actionability	There is no executable code, no commands, and no concrete procedures — the 'Response Approach' is abstract ('Analyze current performance using appropriate profiling and monitoring tools'), matching the 'vague or abstract; describes rather than instructs' anchor.	1 / 3
Workflow Clarity	A 9-step 'Response Approach' sequence exists, but it has no validation checkpoints or error-recovery feedback loops for destructive/batch database operations, capping it at 2 per the rubric's destructive-operation rule.	2 / 3
Progressive Disclosure	Content is well-sectioned by headers, but it is a single monolithic file with a large capability catalog that should be split into references; no bundle files exist, so it is not the one-level-deep, well-signaled structure of score 3.	2 / 3
	Total	6 / 12 Passed

Description

100%

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 strong, well-crafted description: third-person voice, concrete capability list, and an explicit proactive trigger clause covering both what and when. Its only soft spot is a fairly short, somewhat generic trigger-term list, but it clears each dimension's top anchor.

Dimension	Reasoning	Score
Specificity	Lists many concrete actions — 'advanced indexing, N+1 resolution, multi-tier caching, partitioning strategies... complex query analysis, migration strategies, and performance monitoring' — matching the multi-action anchor rather than the single-domain score 2.	3 / 3
Completeness	Explicitly answers both what (the enumerated optimization capabilities) and when ('Use PROACTIVELY for...'), meeting the score 3 'what AND when with explicit triggers' anchor.	3 / 3
Trigger Term Quality	The trigger clause 'Use PROACTIVELY for database optimization, performance issues, or scalability challenges' uses natural phrasings a user would actually say; it is not merely technical jargon like the score 1 anchor.	3 / 3
Distinctiveness Conflict Risk	The 'database optimizer' niche with distinct triggers (performance issues, scalability challenges) is clearly scoped and unlikely to fire for unrelated skills; not generic like the score 1 anchor.	3 / 3
	Total	12 / 12 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
metadata_version	'metadata.version' is missing	Warning

	Total	15 / 16 Passed

Repository: rmyndharis/antigravity-skills
Path: skills/database-optimizer/SKILL.md
Commit: e63f7dd

Reviewed: about 4 hours ago

Table of Contents

Discovery Implementation Validation

Is this your skill?

If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.