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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.

48

Quality

51%

Does it follow best practices?

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SecuritybySnyk

Passed

No findings from the security scan

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

Quality

Content

50%Weight 40%Scale 1-5

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

The body is well-structured as an overview with excellent progressive disclosure — a single well-signaled, one-level-deep reference — and sensible When to Use / Limitations sections. Its weaknesses are low actionability (no concrete guidance in the body itself, everything delegated to the guide) and moderate padding from the duplicated description and persona framing. A brief quick-start section with concrete first steps would make the body actionable on its own.

Suggestions

Add a short quick-start section with one or two concrete first steps (e.g. a minimal cost-check command or a decision checklist for model selection) so the body is actionable without opening the guide.

Remove the verbatim duplication of the frontmatter description in the intro paragraph and trim the motivational persona lines ('You know AI wrappers get a bad rap...') to save tokens.

Add explicit validation/checkpoint framing to the delegation step (e.g. 'verify cost limits and hallucination handling per the Sharp Edges section before shipping') so the workflow has a feedback loop in the body.

DimensionReasoningScore

Conciseness

The body is short but includes padding: the intro paragraph repeats the frontmatter description nearly verbatim, and the persona section ('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') is motivational framing that adds little actionable information. It avoids explaining concepts Claude already knows, but the duplication and persona fluff mean it could be tightened, matching 'mostly efficient but includes some unnecessary explanation'.

3 / 5

Actionability

The body itself contains no concrete code, commands, or specific steps — its only directive is 'Read [the detailed guide](references/detailed-guide.md) before executing this skill', with the rest being role description ('You balance costs with user experience') and a generic expertise bullet list. This matches 'minimal concrete guidance; high-level hints but missing the specific steps to execute'; it is not a 1 because the delegation to the guide is an explicit, correct instruction rather than pure abstraction.

2 / 5

Workflow Clarity

The only sequence given is 'read the guide (fully for end-to-end work, relevant sections for focused work) before executing', which is a clear but minimal workflow with no validation checkpoints or feedback loops — matching 'steps listed but validation gaps; sequence present but checkpoints missing'. Not a 4 because the body provides no checkpoints of its own and the skill's risky areas (cost limits, rate limiting, hallucination handling) are only addressed in the delegated reference.

3 / 5

Progressive Disclosure

The body is a lean overview that delegates all detail to a single, clearly signaled, one-level-deep reference (references/detailed-guide.md), which exists and is well-organized with sectioned headings (Capabilities, Patterns, Sharp Edges, etc.) and no nested references. The body even gives navigation guidance ('For focused work, load the relevant sections; for end-to-end work, read the guide completely'), matching the 'clear overview with well-signaled one-level-deep references' anchor.

5 / 5

Total

13

/

20

Passed

Description

53%Weight 40%Scale 1-5

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 clearly communicates the skill's identity and positioning as a paid AI-wrapper product expertise, with a distinct anti-'thin wrapper' framing. However, it lacks any 'Use when...' trigger guidance and misses natural trigger terms (AI SaaS, GPT product, AI tool) that users would actually say, capping completeness and trigger-term quality. Adding explicit trigger phrases would lift the two heaviest-weighted dimensions.

Suggestions

Append a 'Use when...' clause with concrete trigger phrases, e.g. 'Use when the user wants to build an AI wrapper, GPT product, AI SaaS, or a tool wrapping an LLM API.'

List 2-3 specific capabilities in the description itself (e.g. prompt engineering for products, cost management, rate-limit handling) so the 'what' is concrete rather than one broad action.

Include natural synonym terms users would say ('AI SaaS', 'GPT wrapper', 'AI tool', 'Claude API product') to improve trigger-term coverage and distinctiveness.

DimensionReasoningScore

Specificity

The description names the domain ('products that wrap AI APIs (OpenAI, Anthropic, etc.)') and one broad action ('building... focused tools people will pay for'), which matches the 'names domain and 1-2 concrete actions' anchor. It does not list several specific actions like prompt engineering, cost management, or rate limiting (those appear only in the body), so it is not a 4.

3 / 5

Completeness

The 'what' is clear (build focused, paid AI wrapper products), but there is no 'Use when...' clause or equivalent trigger guidance in the description itself, which caps completeness at 3 per the judging guidelines. Not a 4 because 'when' is entirely absent rather than merely implicit.

3 / 5

Trigger Term Quality

It includes some relevant natural terms ('AI wrapper' implied via 'wrap AI APIs', 'ChatGPT', 'OpenAI, Anthropic'), but misses common variations users would actually say such as 'AI SaaS', 'GPT product', 'AI tool', or 'Claude API product' (which only appear in the body's When to Use section). Good but incomplete keyword coverage places it between anchors 3 and 4, closer to 3 since several common synonyms are absent.

3 / 5

Distinctiveness Conflict Risk

The niche is fairly distinct — 'products that wrap AI APIs... people will pay for' with the explicit 'Not just ChatGPT but different' framing carves out a specific product-building scope with minimal conflict risk against generic AI-assistant skills. Not a 5 because it could still overlap with broader AI product/app-building skills since no concrete trigger phrases distinguish it.

4 / 5

Total

13

/

20

Passed

Validation

93%

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

Validation — 15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

frontmatter_unknown_keys

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

Warning

Total

15

/

16

Passed

Repository
sickn33/agentic-awesome-skills
Reviewed

Table of Contents

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