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ai-sdk

Answer questions about the AI SDK and help build AI-powered features. Use when developers: (1) Ask about AI SDK functions like generateText, streamText, ToolLoopAgent, embed, or tools, (2) Want to build AI agents, chatbots, RAG systems, or text generation features, (3) Have questions about AI providers (OpenAI, Anthropic, Google, etc.), streaming, tool calling, structured output, or embeddings, (4) Use React hooks like useChat or useCompletion. Triggers on: "AI SDK", "Vercel AI SDK", "generateText", "streamText", "add AI to my app", "build an agent", "tool calling", "structured output", "useChat".

76

0.91x
Quality

85%

Does it follow best practices?

Impact

71%

0.91x

Average score across 1 eval scenario

SecuritybySnyk

Passed

No findings from the security scan

SKILL.md
Quality
Evals
Security

Quality

Content

75%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 concise, action-oriented guide that points Claude to version-matched bundled docs and external resources rather than duplicating volatile API details. It is well-structured and executable, with only minor redundancy and loose cross-section workflow sequencing.

Suggestions

Consolidate the repeated 'read the bundled docs' guidance into one place and reference it, to remove redundancy across sections.

Add a single condensed end-to-end workflow (verify install → fetch current model list → read bundled docs for the API → implement → type-check) so the sequence and validation checkpoints read as one loop.

Provide one minimal copy-paste generateText/streamText example guarded by a 'verify against bundled docs' note, to raise actionability without violating the no-memory rule.

DimensionReasoningScore

Conciseness

The body is lean and assumes Claude's competence (e.g. no explanation of what streaming or embeddings are), with short focused sections; minor redundancy such as restating "read the bundled docs" across sections and repeating the no-memory rule keeps it just below a 5.

4 / 5

Actionability

Provides concrete executable commands and paths ("pnpm add ai", "node_modules/ai/docs/", the curl | jq model-listing snippets, "npm view ai version", "AI_GATEWAY_API_KEY"); the deliberate absence of API code examples is justified by the don't-trust-memory principle, leaving only minor gaps.

4 / 5

Workflow Clarity

A clear sequence exists (install ai → read bundled docs → choose/verify models → keep current → run type checker after changes) with checkpoints like "do not guess" and re-checking docs on type errors, but the steps are spread across sections rather than one crisp validate→fix→retry loop.

4 / 5

Progressive Disclosure

Well-organized into clear section headers, with detailed material appropriately deferred one level deep to bundled node_modules docs and external URLs rather than inlined; no bundle files exist, and the single-file structure is clean with only minor organization gaps.

4 / 5

Total

16

/

20

Passed

Description

96%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 specific, complete, and rich in natural trigger terms, clearly delineating the AI SDK's scope and when to invoke the skill. Its only weakness is a couple of broad triggers that could overlap with adjacent skills.

DimensionReasoningScore

Specificity

Names many concrete capabilities — "generateText, streamText, ToolLoopAgent, embed, or tools", "AI agents, chatbots, RAG systems", "streaming, tool calling, structured output, or embeddings", "useChat or useCompletion" — giving comprehensive coverage of the SDK's surface.

5 / 5

Completeness

Explicitly answers both "what" ("Answer questions about the AI SDK and help build AI-powered features") and "when" (a four-part "Use when developers..." list plus an explicit "Triggers on:" clause with concrete trigger phrases).

5 / 5

Trigger Term Quality

Includes both technical terms ("AI SDK", "Vercel AI SDK", "generateText", "streamText", "useChat") and natural user phrases ("add AI to my app", "build an agent", "tool calling", "structured output"), covering synonyms and variations a user would actually say.

5 / 5

Distinctiveness Conflict Risk

The SDK-specific function names (generateText, streamText, useChat) and "Vercel AI SDK" carve a clear niche, but generic triggers like "add AI to my app" and "build an agent" create minor overlap risk with general agent-building skills.

4 / 5

Total

19

/

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.

Validation16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository
vercel/ai
Reviewed

Table of Contents

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