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.
88
88%
Does it follow best practices?
Impact
91%
4.78xAverage score across 3 eval scenarios
Advisory
Suggest reviewing before use
Quality
Discovery
92%Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.
This is a strong description that clearly identifies its domain (Vercel AI SDK) and provides comprehensive trigger terms covering the breadth of the SDK's capabilities. The explicit 'Use when...' clause with a detailed list of scenarios is well-constructed. The main weakness is that many trigger terms are generic AI/ML concepts that could overlap with other skills, though the 'Vercel AI SDK' anchor helps differentiate it.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Lists multiple specific concrete actions and capabilities: chat interfaces, text generation, structured output, tool calling, agents, MCP integration, streaming, embeddings, reranking, image generation, and working with LLM providers. | 3 / 3 |
Completeness | Clearly answers both what ('Vercel AI SDK expert guidance' covering specific capabilities) and when ('Use when building AI-powered features') with an explicit 'Use when...' clause followed by a comprehensive list of trigger scenarios. | 3 / 3 |
Trigger Term Quality | Excellent coverage of natural terms users would say when building AI features: 'chat interfaces', 'text generation', 'structured output', 'tool calling', 'agents', 'streaming', 'embeddings', 'image generation', 'LLM provider', 'Vercel AI SDK'. These are all terms developers naturally use. | 3 / 3 |
Distinctiveness Conflict Risk | While 'Vercel AI SDK' is a distinct niche, many of the trigger terms like 'text generation', 'streaming', 'embeddings', 'image generation', and 'tool calling' are very broad and could easily overlap with other AI/LLM-related skills. The description could conflict with general LLM usage skills or other framework-specific skills. | 2 / 3 |
Total | 11 / 12 Passed |
Implementation
85%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This is a well-structured skill that provides actionable, concrete guidance for working with the Vercel AI SDK. Its strongest aspects are the clear workflow sequences with fallback chains and the excellent progressive disclosure through well-organized references. The main weakness is some verbosity in the cautionary framing, though this is partially justified given the emphasis on not trusting cached knowledge.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Generally efficient but has some unnecessary verbosity. The 'Critical: Do Not Trust Internal Knowledge' section is somewhat heavy-handed, and the explanation 'Everything you know about the AI SDK is outdated or wrong' is repeated conceptually multiple times. The curl command in point 7 is long but justified. Some points like 'Be minimal' are good meta-instructions but could be tighter. | 2 / 3 |
Actionability | Provides concrete, executable commands throughout: specific grep patterns for searching docs, a curl command for fetching model IDs, clear file paths to check (node_modules/ai/docs/, node_modules/ai/src/), specific URL patterns for searching ai-sdk.dev, and explicit package installation commands. The guidance is copy-paste ready. | 3 / 3 |
Workflow Clarity | Clear sequenced workflows with validation checkpoints: Prerequisites establish a clear first step, the numbered list in 'Critical' section provides a clear decision sequence, 'When Typecheck Fails' has an explicit fallback chain (check common-errors → search local → search online), and agent building has a clear detect-framework-first workflow. The typecheck step (point 8) serves as a validation checkpoint. | 3 / 3 |
Progressive Disclosure | Excellent structure with a clear overview in SKILL.md and well-signaled one-level-deep references to common-errors.md, ai-gateway.md, type-safe-agents.md, and devtools.md. The References section at the bottom provides a clean navigation index with brief descriptions. Content is appropriately split between the main file and reference documents. | 3 / 3 |
Total | 11 / 12 Passed |
Validation
72%Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.
Validation — 8 / 11 Passed
Validation for skill structure
| Criteria | Description | Result |
|---|---|---|
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 | 8 / 11 Passed | |
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Table of Contents
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