function-class-generator

Generate complete, production-ready functions and classes from formal specifications, design descriptions, type signatures, or natural language requirements. Use this skill when implementing APIs from specifications, creating data structures from schemas, building classes from UML diagrams, generating code from contracts, or translating design documents into code. Supports multiple programming languages and follows language-specific best practices.

1.16x

Quality

73%

Does it follow best practices?

Impact

94%

1.16x

Average score across 3 eval scenarios

Securityby

Passed

No known issues

Optimize this skill with Tessl

npx tessl skill review --optimize ./skills/function-class-generator/SKILL.md

Quality

Discovery

92%

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-crafted skill description that clearly articulates both capabilities and usage triggers. It uses third person voice correctly and provides specific examples of input types (specifications, schemas, UML diagrams). The main weakness is potential overlap with general code generation skills due to the broad 'natural language requirements' phrase.

Dimension	Reasoning	Score
Specificity	Lists multiple specific concrete actions: 'Generate complete, production-ready functions and classes from formal specifications, design descriptions, type signatures, or natural language requirements.' Clearly describes what kinds of outputs (functions, classes) and inputs (specifications, schemas, UML diagrams, contracts).	3 / 3
Completeness	Clearly answers both what ('Generate complete, production-ready functions and classes') AND when ('Use this skill when implementing APIs from specifications, creating data structures from schemas, building classes from UML diagrams...'). Has explicit 'Use this skill when' clause with multiple trigger scenarios.	3 / 3
Trigger Term Quality	Includes natural keywords users would say: 'specifications', 'APIs', 'schemas', 'UML diagrams', 'contracts', 'design documents', 'type signatures'. These cover common variations of how users describe code generation from formal inputs.	3 / 3
Distinctiveness Conflict Risk	While it specifies formal specifications and design documents as inputs, 'generating code' is broad and could overlap with general coding skills. The focus on 'specifications', 'schemas', and 'UML diagrams' provides some distinction, but 'natural language requirements' is quite generic and could conflict with other code generation skills.	2 / 3
	Total	11 / 12 Passed

Implementation

55%

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

The skill provides excellent actionable guidance with complete, executable code examples and clear workflows, but is severely bloated with unnecessary explanations and lacks any progressive disclosure structure. Claude doesn't need explanations of what type signatures are, what SOLID principles mean, or basic programming concepts. The content would be far more effective at 20% of its current length with references to detailed pattern files.

Suggestions

Reduce content by 70-80% by removing explanations of concepts Claude already knows (type signatures, SOLID principles, basic patterns, what documentation is)

Split detailed patterns (Function from Type Signature, Class from Specification, etc.) into separate reference files like PATTERNS.md or EXAMPLES.md

Move language-specific templates to a separate LANGUAGE_TEMPLATES.md file and reference it from the main skill

Condense the 'Best Practices' and 'Common Patterns' sections to a brief checklist or remove entirely since Claude knows these patterns

Dimension	Reasoning	Score
Conciseness	Extremely verbose at ~600+ lines with extensive explanations Claude already knows (what type signatures are, basic programming concepts, SOLID principles). The document explains obvious patterns and includes redundant information throughout.	1 / 3
Actionability	Provides fully executable, copy-paste ready code examples across multiple languages (Python, TypeScript, Java concepts). Each pattern includes complete implementations with proper error handling and corresponding test suites.	3 / 3
Workflow Clarity	Clear 5-step workflow (Parse → Design → Generate → Document → Test) with explicit validation checkpoints. Each step has concrete examples showing what to extract and produce, with feedback loops for error handling.	3 / 3
Progressive Disclosure	Monolithic wall of text with no references to external files. All content is inline including detailed patterns, language templates, and best practices that could be split into separate reference documents for different use cases.	1 / 3
	Total	8 / 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 (897 lines); consider splitting into references/ and linking	Warning

	Total	10 / 11 Passed

Repository: ArabelaTso/Skills-4-SE
Commit: 0f00a4f

Reviewed: 29 days ago

Table of Contents

Discovery Implementation Validation

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