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ai-elements

Build AI chat interfaces using ai-elements components — conversations, messages, tool displays, prompt inputs, and more. Use when the user wants to build a chatbot, AI assistant UI, or any AI-powered chat interface.

84

8.33x
Quality

76%

Does it follow best practices?

Impact

100%

8.33x

Average score across 3 eval scenarios

SecuritybySnyk

Critical

Do not install without reviewing

Fix and improve this skill with Tessl

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

Quality

Content

68%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 skill body is highly actionable with executable install and usage examples and a clean overview-to-references structure. It is held back by redundant prose that inflates token cost and an install workflow that lacks explicit validation checkpoints and per-section reference navigation.

Suggestions

Remove the duplicated "use them in your application like any other React component" sentence (it appears in both Usage and Example) and trim filler like "the usage feels very natural" to tighten the body.

Turn the Installing Components section into a short numbered sequence with a checkpoint (e.g., confirm files appear under components/ai-elements/) so the workflow has an explicit validation step.

Replace the single trailing "See the references/ folder" line with a short indexed list mapping key components (conversation, message, prompt-input, tool) to their reference files for easier discovery.

DimensionReasoningScore

Conciseness

Mostly efficient with concrete install commands and a full code example, but padded with redundant sentences ("use them in your application like any other React component" appears twice) and unnecessary commentary such as "the usage feels very natural".

3 / 5

Actionability

Provides copy-paste-ready, executable guidance — concrete CLI commands, a complete conversation.tsx example, and a tsconfig.json snippet covering the common installation and usage cases.

5 / 5

Workflow Clarity

The prerequisite → install → use → customize → troubleshoot sequence is present via section ordering, but install steps are prose rather than a numbered sequence and validation checkpoints (e.g., confirming files landed in components/ai-elements/) are only implicit.

3 / 5

Progressive Disclosure

The body is an overview with well-organized sections and a one-level-deep pointer to the references/ folder of ~48 component docs, but the reference set is only blanket-signaled at the end rather than indexed per section.

4 / 5

Total

15

/

20

Passed

Description

83%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.

A concise, well-targeted description that answers both "what" and "when" with concrete triggers and named capabilities. The only weakness is the "and more" catch-all in place of exhaustive component coverage and a few missing natural synonyms.

DimensionReasoningScore

Specificity

Lists several concrete component actions — "conversations, messages, tool displays, prompt inputs" — but the trailing "and more" leaves minor coverage gaps rather than a comprehensive enumeration.

4 / 5

Completeness

Clearly states what it does (build AI chat interfaces with named components) and gives an explicit, concrete "Use when…" trigger clause with multiple specific scenarios.

5 / 5

Trigger Term Quality

Strong natural triggers ("chatbot", "AI assistant UI", "AI-powered chat interface") but misses common synonyms such as "chat UI" or "chat app".

4 / 5

Distinctiveness Conflict Risk

The AI chat UI / shadcn-based component niche is mostly distinct, with only minor overlap risk against generic UI-building skills.

4 / 5

Total

17

/

20

Passed

Validation

100%

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

Validation — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository
vercel/ai-elements
Reviewed

Table of Contents

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