database-schema-designer

Design robust, scalable database schemas for SQL and NoSQL databases. Provides normalization guidelines, indexing strategies, migration patterns, constraint design, and performance optimization. Ensures data integrity, query performance, and maintainable data models.

1.07x

Quality

76%

Does it follow best practices?

Impact

89%

1.07x

Average score across 3 eval scenarios

Securityby

Passed

No known issues

Optimize this skill with Tessl

npx tessl skill review --optimize ./dist/plugins/database-schema-designer/skills/database-schema-designer/SKILL.md

Quality

Discovery

67%

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

This is a well-written description with strong specificity and clear domain focus on database schema design. The main weakness is the absence of explicit trigger guidance ('Use when...') which would help Claude know exactly when to select this skill. Adding natural user phrases would also improve discoverability.

Suggestions

Add a 'Use when...' clause with explicit triggers like 'Use when the user asks about database design, table structures, schema planning, or data modeling'

Include additional natural trigger terms users might say: 'tables', 'ERD', 'entity relationship', 'foreign keys', 'data model', 'database architecture'

Dimension	Reasoning	Score
Specificity	Lists multiple specific concrete actions: 'Design robust, scalable database schemas', 'normalization guidelines', 'indexing strategies', 'migration patterns', 'constraint design', and 'performance optimization'. Uses third person voice correctly.	3 / 3
Completeness	Clearly answers 'what does this do' with detailed capabilities, but lacks an explicit 'Use when...' clause or equivalent trigger guidance. The 'when' is only implied through the domain description.	2 / 3
Trigger Term Quality	Includes relevant terms like 'SQL', 'NoSQL', 'database schemas', 'normalization', 'indexing', 'migration', but misses common user variations like 'tables', 'ERD', 'data model', 'foreign keys', 'primary keys', or file extensions.	2 / 3
Distinctiveness Conflict Risk	Clear niche focused specifically on database schema design with distinct technical domain (SQL/NoSQL, normalization, indexing). Unlikely to conflict with general coding skills or other data-related skills.	3 / 3
	Total	10 / 12 Passed

Implementation

85%

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

This is a well-structured, highly actionable skill with excellent progressive disclosure through collapsible sections. The main weakness is verbosity in explaining concepts Claude already understands (key terms, basic definitions) and some redundant organizational elements (triggers table, commands table) that inflate token count without proportional value.

Suggestions

Remove the 'Key Terms' section entirely - Claude understands normalization, OLTP/OLAP, foreign keys, and indexes

Consolidate or remove the 'Triggers' and 'Commands' tables - these describe natural language patterns Claude can infer from context

Dimension	Reasoning	Score
Conciseness	The skill is comprehensive but includes some unnecessary content like the 'Key Terms' section explaining basic concepts (normalization, OLTP/OLAP, foreign keys) that Claude already knows. The trigger table and command table add bulk without significant value.	2 / 3
Actionability	Provides fully executable SQL code examples throughout, including complete CREATE TABLE statements, migration scripts, and index creation commands. The examples are copy-paste ready and cover multiple scenarios.	3 / 3
Workflow Clarity	The Process Overview clearly sequences the four phases (Analysis → Design → Optimize → Migrate) with explicit steps. The verification checklist provides validation checkpoints, and the migration deep dive includes reversibility requirements and zero-downtime deployment patterns.	3 / 3
Progressive Disclosure	Excellent use of collapsible details sections for deep dives (Normalization, Data Types, Indexing, etc.) keeping the main content scannable. Quick Reference and Anti-Patterns tables provide immediate value while detailed content is one click away.	3 / 3
	Total	11 / 12 Passed

Validation

90%

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 — 10 / 11 Passed

Validation for skill structure

Criteria	Description	Result
skill_md_line_count	SKILL.md is long (688 lines); consider splitting into references/ and linking	Warning

	Total	10 / 11 Passed

Repository: softaworks/agent-toolkit
Commit: 3027f20

Reviewed: 27 days ago

Table of Contents

Discovery Implementation Validation

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