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. This skill covers LLM integration patterns, RAG architecture, prompt engineering that scales, AI UX that users trust, and cost optimization that doesn't bankrupt you. Use when: keywords, file_patterns, code_patterns.

Quality

19%

Does it follow best practices?

Impact

Pending

No eval scenarios have been run

Securityby

Passed

No known issues

Optimize this skill with Tessl

npx tessl skill review --optimize ./.agent/skills/ai-product/SKILL.md

Quality

Discovery

17%

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 suffers from a broken 'Use when' clause containing placeholder text instead of actual triggers, which severely undermines its utility for skill selection. The opening sentence is marketing fluff rather than functional description, and while it mentions relevant AI topics, it lacks concrete action verbs describing what the skill actually does.

Suggestions

Replace the placeholder 'Use when: keywords, file_patterns, code_patterns' with actual trigger terms like 'Use when building LLM-powered features, implementing RAG systems, designing AI chatbots, or optimizing API costs'

Remove the marketing opener and replace with concrete actions: 'Implements LLM integration patterns, designs RAG pipelines, engineers production prompts, builds trustworthy AI interfaces'

Add natural user keywords: 'OpenAI API', 'embeddings', 'vector database', 'token costs', 'hallucination', 'context window'

Dimension	Reasoning	Score
Specificity	Names domain (AI/LLM integration) and lists several areas (RAG architecture, prompt engineering, AI UX, cost optimization), but these are high-level categories rather than concrete actions. No specific verbs describing what the skill actually does.	2 / 3
Completeness	The 'what' is vague (covers topics but doesn't specify actions), and the 'when' is completely broken with placeholder text instead of actual triggers. The description fails to answer either question adequately.	1 / 3
Trigger Term Quality	The 'Use when' clause contains placeholder text ('keywords, file_patterns, code_patterns') instead of actual trigger terms. Terms like 'LLM', 'RAG', 'prompt engineering' appear in the body but the trigger section is broken.	1 / 3
Distinctiveness Conflict Risk	The AI/LLM domain is somewhat specific, and terms like 'RAG architecture' and 'prompt engineering' provide some distinctiveness, but the broad scope ('every product will be AI-powered') and broken triggers create overlap risk.	2 / 3
	Total	6 / 12 Passed

Implementation

22%

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

This skill is essentially a table of contents with a verbose persona preamble. It lacks any actionable content, concrete guidance, or workflow structure in the main file. The sub-skill organization shows promise but the main skill provides no value on its own - it should either include quick-start content or explain how the modules relate.

Suggestions

Add a quick-start section with at least one concrete, executable code example (e.g., basic structured output pattern)

Include a brief decision tree or workflow explaining when to use each sub-skill module

Remove or drastically shorten the persona description - focus on actionable guidance instead

Add a 'Common patterns' section with copy-paste ready code snippets for the most frequent use cases

Dimension	Reasoning	Score
Conciseness	The persona description is somewhat verbose and could be trimmed - Claude doesn't need to be told about debugging at 3am or shipping to millions. However, the overall structure is lean with just links to sub-skills.	2 / 3
Actionability	No concrete code, commands, or executable guidance provided. The skill is entirely abstract, consisting only of a persona description and links to other files with no actionable content in the main skill itself.	1 / 3
Workflow Clarity	No workflow, sequence, or process is defined. The skill provides no guidance on when to use which sub-skill, how they relate to each other, or what order to approach AI product development tasks.	1 / 3
Progressive Disclosure	References to sub-skills are one level deep and clearly organized with good/bad pattern indicators (✓/❌). However, there's no overview content explaining when to use each module or how they fit together - it's just a list of links.	2 / 3
	Total	6 / 12 Passed

Validation

90%

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

Repository: Dokhacgiakhoa/antigravity-ide
Commit: 3395991

Reviewed: 24 days ago

Table of Contents

Discovery Implementation Validation

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