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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

83%

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SecuritybySnyk

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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 lean, actionable, well-organized instruction-style skill body that trusts Claude's competence, uses concrete commands, and routes detail to real one-level-deep references. The main gaps are minor verbosity in the inline model-fetching command and key agent code being deferred to bundled docs.

Suggestions

Trim or factor out the long inline 'curl -s ... | jq' model-fetching pipeline into a reference file to improve conciseness, since it is verbose and time-sensitive (model IDs change).

Add a minimal executable ToolLoopAgent code skeleton inline so the primary agent-creation pattern does not depend on grepping bundled docs.

Close the typecheck-failure feedback loop explicitly (e.g., 'after fixing, re-run typecheck until it passes') to make error-recovery checkpoints explicit across all flows.

DimensionReasoningScore

Conciseness

Mostly lean and assumes Claude's competence ('Everything you know... is outdated'), but the lengthy inline curl/jq model-fetching command and slightly padded prerequisites add minor verbosity.

4 / 5

Actionability

Concrete executable commands throughout (pnpm add ai, grep node_modules/ai/docs/, curl|jq pipeline, typecheck), with the minor gap that the core ToolLoopAgent code is deferred to docs rather than shown.

4 / 5

Workflow Clarity

Clear sequenced workflows with validation checkpoints (typecheck after changes; 'When Typecheck Fails' fallback chain: grep common-errors -> search src/docs -> search web), with minor gaps in fully closed error-recovery loops.

4 / 5

Progressive Disclosure

Body is a concise overview pointing via clearly-signaled markdown links to four real one-level-deep reference files (common-errors.md, ai-gateway.md, type-safe-agents.md, devtools.md), organized with a dedicated References section.

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 specific, well-structured description that clearly states both capabilities and explicit trigger conditions with comprehensive action coverage. Minor overlap risk from the broad 'any LLM provider' framing keeps distinctiveness just below the top anchor.

DimensionReasoningScore

Specificity

Lists many concrete actions/features (chat interfaces, text generation, structured output, tool calling, agents, MCP integration, streaming, embeddings, reranking, image generation), matching the comprehensive-coverage anchor.

5 / 5

Completeness

Explicitly answers both what ('Vercel AI SDK expert guidance') and when ('Use when building AI-powered features — ...') with concrete trigger phrases.

5 / 5

Trigger Term Quality

Strong natural keywords users would say (tool calling, streaming, structured output, agents), but missing some synonyms/extensions of common variations.

4 / 5

Distinctiveness Conflict Risk

Clear Vercel AI SDK niche with mostly distinct triggers, but the broad 'any LLM provider' phrasing and plugin-relative related skills create minor overlap risk.

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.

Validation14 / 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
Reviewed

Table of Contents

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