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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.

51

Quality

Does it follow best practices?

Impact

No eval scenarios have been run

SecuritybySnyk

Passed

No known issues

SKILL.md
Quality
Evals
Security

Quality

Content

65%

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

The body is highly actionable, packed with concrete, executable code for the core AI-wrapper concerns, but it is verbose and repetitive with no progressive disclosure via reference files. Workflow sequencing lacks explicit validation checkpoints, capping clarity at the middle anchor.

Suggestions

Split the detailed pattern sections (cost management, rate limiting, hallucination handling, latency) into reference files and keep SKILL.md as a lean overview with one-level-deep links.

Remove duplicated headings and trim explanations of concepts Claude already knows (exponential backoff, caching) to tighten conciseness.

Add explicit validation/retry checkpoints to the collaboration workflows and replace bare 'Recommended fix:' labels with concrete inline steps.

DimensionReasoningScore

Conciseness

Mostly efficient with concrete code and tables, but padded by duplicated section headings (e.g. 'AI Product Architecture' appears as both ### and ##), restatements of known concepts like exponential backoff and caching, and dated version strings ('claude-3-haiku-20240307', GPT-4o).

2 / 3

Actionability

Provides many concrete, executable JavaScript examples using the real Anthropic SDK (messages.create, streaming, retry/backoff, queueing, cost tracking, output validation) with specific parameters, going well beyond pseudocode.

3 / 3

Workflow Clarity

Sequences exist (numbered collaboration workflows, the commented Basic Implementation steps), but validation checkpoints and feedback loops are absent, and 'Recommended fix:' labels jump straight into a new section header rather than inline steps.

2 / 3

Progressive Disclosure

The ~688-line SKILL.md is a single monolithic file with no bundle references; it is organized into sections, but detailed pattern content (cost, rate limits, hallucinations, latency) that should be split into reference files is all inline.

2 / 3

Total

9

/

12

Passed

Description

50%

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 defines a clear niche and uses natural third-person voice, but it is role-oriented rather than action-oriented and omits any explicit 'when to use' trigger guidance. It is solid but not exemplary, sitting at the middle anchor across all dimensions.

Suggestions

Add an explicit 'Use when...' clause listing trigger terms (e.g., AI wrapper, GPT product, AI tool, AI SaaS) to raise completeness and distinctiveness.

Replace abstract role phrasing with concrete actions the skill performs (e.g., 'designs prompt templates, tracks token costs, retries rate-limited API calls') to improve specificity.

Include the natural keyword variations users actually say ('AI wrapper', 'AI SaaS') to broaden trigger-term coverage.

DimensionReasoningScore

Specificity

Names the domain and some actions ('building products that wrap AI APIs', 'solve specific problems with AI') but stays at the level of roles rather than listing multiple concrete actions, matching anchor 2.

2 / 3

Completeness

Clearly states what the skill does but lacks any 'Use when...' or equivalent explicit trigger guidance, which the guidelines say caps completeness at 2.

2 / 3

Trigger Term Quality

Includes relevant natural terms ('AI APIs', 'OpenAI', 'Anthropic', 'ChatGPT') but misses common variations a user would say ('AI wrapper', 'GPT product', 'AI SaaS', 'AI tool') that appear only in the body, so coverage is partial.

2 / 3

Distinctiveness Conflict Risk

The 'AI wrapper product' niche is fairly specific, but without explicit triggers it could overlap with adjacent skills like micro-saas-launcher or llm-architect noted in the body.

2 / 3

Total

8

/

12

Passed

Validation

87%

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

Validation14 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

skill_md_line_count

SKILL.md is long (689 lines); consider splitting into references/ and linking

Warning

frontmatter_unknown_keys

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

Warning

Total

14

/

16

Passed

Repository
boisenoise/skills-collections
Reviewed

Table of Contents

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