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ai-wrapper-product

You know AI wrappers get a bad rap, but the good ones solve real problems. You build products where AI is the engine, not the gimmick. You understand prompt engineering is product development. You balance costs with user experience. You create AI products people actually pay for and use daily.

20

Quality

7%

Does it follow best practices?

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SecuritybySnyk

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tessl review fix ./skills/ai-wrapper-product/SKILL.md

The canonical home for this skill is ai-wrapper-product in sickn33/antigravity-awesome-skills

SKILL.md
Quality
Evals
Security

Quality

Content

14%Scale 1-3

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

This skill is a verbose, poorly organized collection of loosely related AI wrapper concepts that reads more like a blog post than actionable guidance. It suffers from significant redundancy, incomplete code examples, broken internal references, and lacks any coherent workflow or progressive disclosure structure. The content would benefit from dramatic trimming, completing code examples, establishing a clear build workflow, and splitting detailed patterns into referenced sub-files.

Suggestions

Remove the capabilities bullet list, role re-statement, and 'When to Use' tautology — these waste tokens without adding actionable value

Create a clear sequential workflow (e.g., 1. Design prompt templates → 2. Implement with validation → 3. Add cost tracking → 4. Set usage limits → 5. Test end-to-end) with explicit validation checkpoints at each stage

Fix broken Sharp Edges references — either create the referenced sections or link to separate files, and move detailed code examples into referenced sub-files for progressive disclosure

Complete all code examples with necessary imports and function definitions (e.g., parseOutput, getUserLimits, startOfMonth) so they are copy-paste executable

DimensionReasoningScore

Conciseness

Extremely verbose with significant redundancy. The role description is repeated from the frontmatter. Capability bullet lists add no value Claude doesn't already know. Anti-patterns use fragmented sentence style that wastes tokens while being less clear. The 'When to Use' section is a meaningless tautology. Model selection tables contain time-sensitive pricing data that will become stale.

1 / 3

Actionability

Contains some executable code examples (API calls, cost tracking, prompt templates) which is good, but much of the content is conceptual rather than actionable. The architecture diagram is ASCII pseudocode, the Sharp Edges table references sections that don't exist (e.g., '## Controlling AI Costs'), and many code snippets are incomplete (missing imports, undefined functions like parseOutput, getUserLimits).

2 / 3

Workflow Clarity

There is no clear multi-step workflow for building an AI wrapper product. The content presents disconnected patterns without sequencing them into a coherent process. No validation checkpoints exist for the overall product development flow. The basic implementation shows numbered steps within a single function but lacks error recovery or feedback loops for the broader workflow.

1 / 3

Progressive Disclosure

Monolithic wall of text with everything inline. No references to external files for detailed content. The Sharp Edges table references section headers that don't exist in the document. The 'Related Skills' section mentions other skills but provides no links. All code examples, tables, and patterns are dumped into a single file with no navigation structure.

1 / 3

Total

5

/

12

Passed

Description

0%Scale 1-3

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 description reads as a motivational persona statement written in second person ('You know', 'You build', 'You understand') rather than a functional skill description. It provides no concrete actions, no explicit trigger guidance, and no clear scope, making it essentially unusable for skill selection among a set of available skills.

Suggestions

Rewrite in third person and list specific concrete actions the skill performs, e.g., 'Designs AI-powered product architectures, engineers prompts for production use, implements cost-optimization strategies for LLM API calls, and builds user-facing AI features.'

Add an explicit 'Use when...' clause with natural trigger terms, e.g., 'Use when building AI wrapper products, designing prompt pipelines, optimizing LLM costs, or creating SaaS products powered by language models.'

Remove motivational/opinion language ('bad rap', 'not the gimmick', 'people actually pay for') and replace with factual capability statements that help Claude distinguish this skill from other AI-related skills.

DimensionReasoningScore

Specificity

The description uses vague, abstract language like 'solve real problems', 'AI is the engine', and 'balance costs with user experience'. No concrete actions are listed — there's nothing about what the skill actually does (e.g., build APIs, design prompts, create pricing models).

1 / 3

Completeness

The description fails to answer both 'what does this do' and 'when should Claude use it'. There is no 'Use when...' clause or equivalent trigger guidance, and the 'what' is entirely absent — it reads like a persona statement rather than a skill description.

1 / 3

Trigger Term Quality

The only potentially relevant keywords are 'AI wrappers' and 'prompt engineering', but these are buried in motivational language. Terms like 'bad rap', 'gimmick', and 'people actually pay for' are not natural trigger terms a user would use when seeking help with a task.

1 / 3

Distinctiveness Conflict Risk

The description is extremely generic — 'build products where AI is the engine' could overlap with virtually any AI-related skill. There are no distinct triggers or a clear niche that would differentiate this from other AI development or product skills.

1 / 3

Total

4

/

12

Passed

Validation

90%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation10 / 11 Passed

Validation for skill structure

CriteriaDescriptionResult

frontmatter_unknown_keys

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

Warning

Total

10

/

11

Passed

Repository
administrakt0r/AI-Agents-Safe-Coding-Skills
Reviewed

Table of Contents

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