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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.

82

1.18x
Quality

88%

Does it follow best practices?

Impact

95%

1.18x

2 of 3 eval scenarios. Add 1 more for a full score.

SecuritybySnyk

Passed

No findings from the security scan

The canonical home for this skill is ai-sdk in vercel/ai

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, disciplined body built around a coherent philosophy: never trust memory, use the version-matched bundled docs as source of truth, and verify with the type checker. It is lean and well-organized, with concrete lookup and versioning commands; the residual weaknesses are mild redundancy in the memory-warning section and the absence of any inline code example for common tasks.

Suggestions

Collapse the three restatements in "Critical: Do Not Trust Your Own Memory" into a single directive plus the bolded rule to tighten conciseness.

Inline one minimal, version-flagged code example for the most common case (e.g., a streamText chat route) so the skill is not purely a pointer to external docs, keeping it short since bundled docs remain the source of truth.

Make the "After Making Changes" loop explicit (type check → on error, re-check bundled docs → fix → re-run) to elevate the workflow's validation checkpoint.

DimensionReasoningScore

Conciseness

The body assumes Claude's competence and is largely terse and imperative, but the "Do Not Trust Your Own Memory" section makes its single point three times ("Whatever you remember… is likely outdated", "Your training data almost certainly contains obsolete APIs", "Never write AI SDK code from memory"), which is trimmable padding.

4 / 5

Actionability

Copy-paste-ready commands are present (the gateway model-list curl with jq, "npm view ai version", "pnpm add ai --filter <pkg>", node_modules docs paths, the ".md" URL trick), and deferring SDK code to version-matched bundled docs is explicitly justified — but no inline usage example exists for even the most common case, leaving minor gaps.

4 / 5

Workflow Clarity

Each section carries a numbered sequence (bundled-docs lookup steps 1–5, gateway setup 1–3) and a feedback loop exists ("Run the project's type checker… re-check the current docs and source when they occur", plus the version-comparison and "say so explicitly — do not guess" checkpoints), though the overall build flow lacks an explicit validate-and-retry loop.

4 / 5

Progressive Disclosure

With no bundle files, the ~74-line body is cleanly sectioned so no content needs splitting, and every pointer is one level deep and clearly signaled (node_modules/ai/docs/, @ai-sdk/<name>/docs/, ai-sdk.dev/docs) — a clear, easily navigable overview.

5 / 5

Total

17

/

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.

A strong description: it names a distinct niche, comprehensively enumerates concrete capabilities, and includes an explicit "Use when…" trigger clause with natural user phrasing. The only weakness is the broad "any LLM provider" clause, which slightly widens the trigger surface beyond the skill's core niche.

DimensionReasoningScore

Specificity

The description lists ten concrete capabilities ("chat interfaces, text generation, structured output, tool calling, agents, MCP integration, streaming, embeddings, reranking, image generation"), matching the anchor for multiple specific concrete actions with comprehensive coverage of the SDK's surface.

5 / 5

Completeness

It explicitly answers both "what" ("Vercel AI SDK expert guidance" plus the capability list) and "when" ("Use when building AI-powered features — … or working with any LLM provider"), mirroring the top anchor's what+when structure with concrete trigger phrases.

5 / 5

Trigger Term Quality

Natural user phrases are comprehensively covered — "chat interfaces", "tool calling", "streaming", "embeddings", "image generation", "working with any LLM provider" — the terms a user building AI features would actually say, with no jargon-only or generic filler.

5 / 5

Distinctiveness Conflict Risk

The Vercel AI SDK identity is a clear, distinct niche, but the closing trigger "or working with any LLM provider" is broad and creates minor overlap risk with other provider-specific LLM skills, keeping it just below the minimal-conflict anchor.

4 / 5

Total

19

/

20

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.

Validation — 13 / 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

Path

skills/ai-sdk/SKILL.md

Reviewed

Table of Contents

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