ai-wrapper-product

Expert in building products that wrap AI APIs (OpenAI, Anthropic, etc.) into focused tools people will pay for. Not just 'ChatGPT but different' - products that solve specific problems with AI. Cov...

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npx tessl i github:boisenoise/skills-collections --skill ai-wrapper-product

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Overall
score

61%

Review — 49%

Does it follow best practices?

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Validation — 10 / 11 Passed

Validation for skill structure

SKILL.md

Review

Evals

Discovery

33%

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 shows promise with its specific focus on AI API wrapper products and mentions concrete providers, but it is critically truncated ('Cov...'), making full evaluation impossible. It lacks an explicit 'Use when...' clause and the incomplete text prevents assessment of full capability coverage and trigger terms.

Suggestions

Complete the truncated description - the current text cuts off mid-word, losing critical information

Add an explicit 'Use when...' clause with trigger terms like 'AI wrapper', 'monetize AI', 'SaaS product', 'API integration business'

List specific concrete actions such as 'design pricing strategies, validate product-market fit, structure API cost management, build user-facing AI features'

Dimension	Reasoning	Score
Specificity	Names the domain (AI API wrapper products) and hints at actions ('building products', 'solve specific problems'), but the description is truncated and doesn't list multiple concrete actions like 'design pricing models, validate market fit, structure API calls'.	2 / 3
Completeness	Partially addresses 'what' (building AI wrapper products) but is truncated and has no visible 'Use when...' clause or explicit trigger guidance. The incomplete description cannot satisfy the completeness requirement.	1 / 3
Trigger Term Quality	Includes relevant keywords like 'OpenAI', 'Anthropic', 'AI APIs', 'ChatGPT', but the description is cut off ('Cov...') so we can't assess full coverage. Missing natural user terms like 'SaaS', 'monetize', 'AI startup', 'wrapper app'.	2 / 3
Distinctiveness Conflict Risk	The focus on 'AI API wrapper products' and specific providers (OpenAI, Anthropic) provides some distinctiveness, but 'building products' is broad enough to potentially overlap with general product development or coding skills.	2 / 3
	Total	7 / 12 Passed

Implementation

65%

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

This skill provides solid, actionable code examples for building AI wrapper products with good coverage of cost management and prompt engineering. However, it lacks explicit validation workflows and feedback loops for error recovery, and the progressive disclosure is incomplete with broken internal references. The content could be more concise by removing the introductory framing and redundant capabilities list.

Suggestions

Add explicit validation checkpoints to the wrapper stack workflow (e.g., 'Validate API response schema before parsing, retry on failure, fallback to cached response after 3 attempts')

Fix Sharp Edges section references - either create the referenced sections (## Controlling AI Costs, ## Handling Rate Limits) or link to actual files

Remove the introductory paragraph and capabilities list - the patterns section already demonstrates these capabilities through concrete examples

Add a feedback loop example for handling API failures: validate -> log error -> retry with backoff -> fallback model -> graceful degradation

Dimension	Reasoning	Score
Conciseness	The content is reasonably efficient but includes some unnecessary framing ('You know AI wrappers get a bad rap') and the capabilities list is somewhat redundant given the detailed patterns that follow. Some sections could be tightened.	2 / 3
Actionability	Provides fully executable JavaScript code examples with real API calls, concrete cost calculation functions, usage tracking implementations, and specific model selection tables. Code is copy-paste ready with proper imports and error handling.	3 / 3
Workflow Clarity	The wrapper stack diagram shows clear sequence, but validation checkpoints are implicit rather than explicit. Missing feedback loops for handling API failures beyond basic retry mention. The cost management section lacks explicit 'validate then proceed' patterns.	2 / 3
Progressive Disclosure	Content is organized into logical sections with clear headers, but the Sharp Edges section references solutions (## Controlling AI Costs) that don't exist as separate files or clearly marked sections. Related Skills mentions other skills but no actual file references for deeper content.	2 / 3
	Total	9 / 12 Passed

Validation

91%

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
frontmatter_unknown_keys	Unknown frontmatter key(s) found; consider removing or moving to metadata	Warning

	Total	10 / 11 Passed

Reviewed: 7 days ago

Table of Contents

Discovery Implementation Validation

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