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ai-sdk

Vercel AI SDK expert guidance. Use when building AI-powered features — chat interfaces, text generation, structured output, tool calling, agents, MCP integration, streaming, embeddings, reranking, image generation, or working with any LLM provider.

96

4.78x
Quality

100%

Does it follow best practices?

Impact

91%

4.78x

Average score across 3 eval scenarios

SecuritybySnyk

Advisory

Suggest reviewing before use

SKILL.md
Quality
Evals
Security

Quality

Content

100%

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

The body is lean, actionable, and well-structured with clear workflows and an explicit validation feedback loop. Progressive disclosure is handled cleanly through real one-level-deep reference files.

DimensionReasoningScore

Conciseness

Lean, directive prose that assumes Claude's competence — it does not explain what the AI SDK is or basic programming concepts, and every section earns its tokens.

3 / 3

Actionability

Provides concrete executable commands such as `grep "query" node_modules/ai/docs/`, the model-listing curl, and `pnpm add ai`, giving copy-paste-ready direction.

3 / 3

Workflow Clarity

Multi-step processes are explicitly sequenced with a validation feedback loop (typecheck fails → grep common-errors.md → search source → search docs) and a numbered nine-step working checklist.

3 / 3

Progressive Disclosure

Body is a concise overview with four well-signaled, one-level-deep references (common-errors.md, ai-gateway.md, type-safe-agents.md, devtools.md), all of which exist as real bundle files and are listed in a References section.

3 / 3

Total

12

/

12

Passed

Description

100%

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, well-triggered, and clearly distinguishes the skill's niche. It cleanly answers both what the skill does and when to invoke it.

DimensionReasoningScore

Specificity

Lists multiple specific concrete capabilities — "chat interfaces, text generation, structured output, tool calling, agents, MCP integration, streaming, embeddings, reranking, image generation" — rather than vague language.

3 / 3

Completeness

Explicitly answers both what ("Vercel AI SDK expert guidance" plus the capability list) and when ("Use when building AI-powered features — ...").

3 / 3

Trigger Term Quality

Natural terms a user would say ("chat interfaces", "streaming", "tool calling", "image generation") are well covered alongside the AI SDK framing.

3 / 3

Distinctiveness Conflict Risk

Scoped to the Vercel AI SDK with a distinct niche (AI-powered features and LLM providers), making conflicts with unrelated skills unlikely.

3 / 3

Total

12

/

12

Passed

Validation

81%

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

Validation13 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

metadata_version

'metadata.version' is missing

Warning

metadata_field

'metadata' should map string keys to string values

Warning

frontmatter_unknown_keys

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

Warning

Total

13

/

16

Passed

Repository
vercel/vercel-plugin
Reviewed

Table of Contents

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