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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.

68

Quality

85%

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SecuritybySnyk

Low

Low-risk findings worth noting

SKILL.md
Quality
Evals
Security

Quality

Content

78%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.

A well-structured, docs-driven skill body: lean, concrete commands, an explicit typecheck-failure recovery loop, and clean one-level-deep references that all resolve. Its main gaps are minor verbosity and a few spots that defer to doc search instead of providing code, plus a dead empty providers.md in the bundle.

Suggestions

Consolidate the install-only-the-ai-package rule (stated in both Prerequisites and rule 1) and split the long run-on model-ID rule into a short command plus one-line guidance to tighten conciseness.

Replace the deferral-style guidance in 'Creating Agents' and 'Consuming Agents' with one minimal copy-paste example each (e.g., a ToolLoopAgent snippet and one framework route/hook pair), pointing to references for the rest.

Remove or populate the empty, unreferenced references/providers.md so the bundle contains no dead files.

DimensionReasoningScore

Conciseness

The body is lean and imperative with no explanation of concepts Claude already knows; minor trimmable fat remains (the install-only-ai rule is stated twice, and item 7 is a long run-on sentence), placing it at 'efficient; minor instances of over-explanation' rather than 'every token earns its place'.

4 / 5

Actionability

Mostly executable guidance: concrete grep targets, a copy-paste `curl ... | jq` model-listing command, exact install commands, and an explicit typecheck step. A few sections ('Always use the ToolLoopAgent pattern. Search ... for current agent creation APIs'; framework-specific consumption) defer to searching rather than giving code — a defensible anti-staleness choice that keeps it above the pseudocode anchor.

4 / 5

Workflow Clarity

Clear sequencing (prerequisites → verify-against-source rules → version-split doc finding) with a validation checkpoint ('Run typecheck after changes') and an explicit error-recovery loop for typecheck failures (grep common-errors.md → local src/docs → web docs). Not 5 because the flow is spread across parallel sections rather than one coherent sequence, and the framework-specific consumption path is only sketched.

4 / 5

Progressive Disclosure

A concise overview with a labeled References section; all four referenced files (common-errors.md, ai-gateway.md, type-safe-agents.md, devtools.md) exist in references/ and are one level deep (none reference further files). The only wart is an empty, unreferenced providers.md in the bundle — not enough to leave the top anchor, which the body itself satisfies.

5 / 5

Total

17

/

20

Passed

Description

88%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 strong description with comprehensive, specific capability coverage and an explicit what/when structure. Its weaknesses are a broad 'any LLM provider' clause that dilutes distinctiveness and a few missing natural trigger terms (useChat, chatbot).

DimensionReasoningScore

Specificity

Lists ten concrete capability areas ('chat interfaces, text generation, structured output, tool calling, agents, MCP integration, streaming, embeddings, reranking, image generation'), matching the comprehensive-coverage anchor; the only soft spot is the slightly abstract 'expert guidance' framing, which is not enough to drop to 4.

5 / 5

Completeness

Clearly answers what ('Vercel AI SDK expert guidance') and when ('Use when building AI-powered features — ...') with explicit concrete trigger phrases, matching the top anchor; the when-clause is fully explicit, so 4's 'could be more explicit' does not apply.

5 / 5

Trigger Term Quality

Good natural-keyword coverage ('tool calling', 'streaming', 'embeddings', 'MCP', 'LLM provider', 'chat interfaces'), but common user phrasings like 'useChat', 'useCompletion', and 'chatbot' are missing, so it fits the 'good coverage, a few natural terms missing' anchor rather than the synonym-comprehensive anchor.

4 / 5

Distinctiveness Conflict Risk

'Vercel AI SDK' establishes a clear niche, but the trailing 'or working with any LLM provider' broadens the trigger to any LLM work (e.g., direct OpenAI SDK or LangChain use), creating minor overlap risk with closely related skills.

4 / 5

Total

18

/

20

Passed

Validation

87%

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

Validation — 14 / 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

Total

14

/

16

Passed

Repository

openai/plugins

Path

plugins/vercel/skills/ai-sdk/SKILL.md

Reviewed

Table of Contents

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