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database-architect

Expert database architect specializing in data layer design from scratch, technology selection, schema modeling, and scalable database architectures. Masters SQL/NoSQL/TimeSeries database selection, normalization strategies, migration planning, and performance-first design. Handles both greenfield architectures and re-architecture of existing systems. Use PROACTIVELY for database architecture, technology selection, or data modeling decisions.

56

Quality

63%

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tessl review fix ./skills/database-architect/SKILL.md
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 body is well-sectioned and covers the role comprehensively, but it is a monolithic catalog of knowledge Claude already possesses with no progressive disclosure into reference files and only high-level process guidance. Validation exists but is not wired into the workflow as a checkpoint.

Suggestions

Move the Capabilities catalog into one or more reference files (e.g. references/technologies.md, references/patterns.md) and keep SKILL.md as a concise overview with one-level-deep links, shedding the bulk of pre-existing-knowledge enumeration.

Trim or remove sections that restate common knowledge (Knowledge Base, much of Capabilities) so every remaining token earns its place; assume Claude knows standard database products and concepts.

Add concrete decision aids to the workflow — a technology-selection decision matrix, an example schema/ERD snippet, and a sample migration plan with rollback — and embed a 'validate in staging' checkpoint directly into the Response Approach steps rather than only in the Safety section.

DimensionReasoningScore

Conciseness

The Capabilities section is a ~140-line catalog enumerating database products and concepts Claude already knows (PostgreSQL, MongoDB, Redis, B-tree/GIN/BRIN indexes, ACID, CAP, saga patterns, isolation levels) — noticeably verbose with several padded reference-list sections, though it is structured as a catalog rather than explanatory prose, keeping it just above the score-1 anchor.

2 / 5

Actionability

A sequenced 10-step 'Response Approach' and an explicit 'Output Examples' deliverable list provide some concrete guidance on what to produce, but the steps are high-level ('Recommend technology ... with rationale', 'Design schema') with no decision matrices, concrete criteria, or example outputs, leaving key details missing.

3 / 5

Workflow Clarity

A clear sequence exists ('Instructions' 4 steps, 'Response Approach' 10 steps), but validation is only implicit — staging validation appears in the separate 'Safety' section rather than as an embedded checkpoint, and migration planning is a database operation, so per the rubric cap workflow clarity stays at 3.

3 / 5

Progressive Disclosure

No bundle files exist and the body contains zero external file references; the large Capabilities catalog clearly belongs in separate reference files but is fully inlined into a single monolithic ~250-line SKILL.md, matching the score-2 anchor of content that should be split being inlined.

2 / 5

Total

10

/

20

Passed

Description

88%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 is strong: it clearly states capabilities, explicitly provides a 'Use PROACTIVELY' trigger clause, and carves a recognizable niche. The only gap is slightly jargon-leaning trigger phrasing and minor overlap with sibling database skills.

DimensionReasoningScore

Specificity

Lists multiple specific concrete action areas — 'data layer design from scratch, technology selection, schema modeling, ... normalization strategies, migration planning, and performance-first design' — giving comprehensive coverage of the database-architecture domain, matching the score-5 anchor.

5 / 5

Completeness

Explicitly answers both what ('Expert database architect specializing in data layer design ...') and when ('Use PROACTIVELY for database architecture, technology selection, or data modeling decisions.'), matching the score-5 anchor of clear what-and-when with concrete trigger phrases.

5 / 5

Trigger Term Quality

Good natural-term coverage ('database architecture', 'data modeling', 'schema modeling', 'migration', 'SQL/NoSQL/TimeSeries'), but 'technology selection' is slightly jargon-leaning and common user phrasings like 'choose/pick a database' or 'database design' are not present, so it sits just below the comprehensive anchor.

4 / 5

Distinctiveness Conflict Risk

The 'greenfield architectures and re-architecture' framing carves a clear niche distinct from pure tuning or ops, but the triggers ('database architecture', 'technology selection') still overlap with closely related skills like database-optimizer and database-admin, so it is mostly distinct with minor overlap risk.

4 / 5

Total

18

/

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.

Validation15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

metadata_version

'metadata.version' is missing

Warning

Total

15

/

16

Passed

Repository
rmyndharis/antigravity-skills
Reviewed

Table of Contents

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