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ai-product

Every product will be AI-powered. The question is whether you'll build it right or ship a demo that falls apart in production.

34

Quality

30%

Does it follow best practices?

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Adds up to 20 points to the overall score

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SecuritybySnyk

Passed

No findings from the security scan

Fix and improve this skill with Tessl

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

Quality

Content

40%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 a clean, correctly structured pointer file — real reference, one level deep, sensibly signaled — but it over-delegates: it contains no concrete guidance, steps, or validation checkpoints of its own, and pads itself with a duplicated tagline and circular When-to-Use boilerplate. It works as a table of contents, not as a skill.

Suggestions

Replace the circular "When to Use" section with concrete trigger conditions (LLM feature build, RAG design, prompt versioning, AI cost debugging) and delete the tagline duplicated from the frontmatter.

Add a per-topic routing list naming the guide's sections (e.g., "Patterns → structured output/streaming/circuit breakers; Sharp Edges → common failure modes; Validation Checks → pre-ship checklist") so "load the relevant sections" is actionable.

Consider splitting the 746-line guide into separate reference files (patterns, sharp-edges, validation) and linking each from the body, which would raise progressive disclosure to anchor 5.

DimensionReasoningScore

Conciseness

The ~20-line body is brief and explains nothing Claude already knows, but it wastes tokens: the opening tagline is duplicated verbatim from the frontmatter, and "Use this skill when the request clearly matches the capabilities and patterns described above" is circular boilerplate that adds no information. Mostly efficient with some unnecessary padding, matching anchor 3.

3 / 5

Actionability

The only concrete instruction in the body is "Read [the detailed guide](references/detailed-guide.md) before executing this skill"; everything else describes scope ("This skill covers LLM integration patterns, RAG architecture...") rather than instructing. The real executable content (code patterns, validation snippets) lives entirely in the reference, so the body alone offers minimal concrete guidance — anchor 2, not 1, because the pointer is a real, specific, working instruction.

2 / 5

Workflow Clarity

No multi-step process is sequenced in the body — no numbered steps, no validation checkpoints; it defers wholesale to the guide's "safety, prerequisites, and validation requirements" without stating any of them. A rough single directive (read the guide first, fully or by section) exists, but the workflow as written has large gaps, matching anchor 2. This is not a simple single-action skill — it claims a multi-topic procedure — so the simple-skill exception does not apply.

2 / 5

Progressive Disclosure

The body is a genuine overview with a clearly signaled, one-level-deep reference: "## Detailed Guide → Read [the detailed guide](references/detailed-guide.md)" with guidance on loading sections vs. reading completely, and references/detailed-guide.md exists and is well-sectioned (Principles, Patterns, Sharp Edges, Validation Checks). Not a 5 because a single 746-line guide bundles four distinct topic areas that could be split into separate reference files, and the body gives no per-topic pointers to help route focused work despite telling the reader to "load the relevant sections".

4 / 5

Total

11

/

20

Passed

Description

20%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 is a marketing tagline rather than a capability description: it names no concrete actions, includes no trigger guidance, and uses second-person voice. A user (or Claude) reading only the frontmatter cannot tell what the skill does or when to invoke it, so it would rarely be selected by intent.

Suggestions

Rewrite in third person listing concrete capabilities, e.g.: "Designs and hardens LLM-powered product features: integration patterns (structured output, streaming, circuit breakers), RAG architecture, prompt versioning and testing, AI UX, and cost optimization."

Append an explicit trigger clause with natural vocabulary: "Use when building or debugging LLM/AI features, designing RAG pipelines, versioning prompts, or optimizing AI API costs."

Drop the rhetorical slogan ("The question is whether you'll build it right...") — it consumes the description budget without adding selectable information.

DimensionReasoningScore

Specificity

"Every product will be AI-powered. The question is whether you'll build it right or ship a demo that falls apart in production" contains no concrete capability actions — it is a motivational slogan, pure abstract language. It does gesture at a domain (building AI-powered products), which keeps it from being indistinguishable from a totally generic hook, but the second-person "you'll build it right" triggers the rubric's voice penalty (base fit between anchors 1 and 2, reduced by 1).

1 / 5

Completeness

The 'what' is extremely vague (it never states what the skill does — the capability list lives in the body, not the description) and the 'when' is entirely absent, matching anchor 2 ('has a vague what and no when'). It cannot reach 3 because even the 'what' is a slogan rather than a stated capability, and the missing 'Use when' clause caps completeness at 3 regardless.

2 / 5

Trigger Term Quality

The only candidate keywords are "AI-powered", "build", and "production" — one or two generic terms with no natural phrases a user would say when needing this skill (no "LLM integration", "RAG", "prompt engineering", "AI feature", or any 'Use when...' phrasing). Not a 1 because "AI-powered" and "production" are at least words users naturally use, but all the skill's actual trigger vocabulary (LLM, RAG, prompts) is absent from the description.

2 / 5

Distinctiveness Conflict Risk

"Every product will be AI-powered" is very broad and would collide with any LLM/prompt/RAG/ML-adjacent skill, matching anchor 2's high-overlap profile. Not a 1 because it is at least anchored to the AI-product niche rather than being fully generic across all skills.

2 / 5

Total

7

/

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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