skills / vercel / ai / ai-sdk

AI SDK

A practical implementation skill for shipping AI-powered features with robust SDK patterns, model wiring, and production-safe integration steps.

Source description: Answer questions about the AI SDK and help build AI-powered features. Use when developers: (1) Ask about AI SDK functions like generateText, streamText, ToolLoo...

npx skills add https://github.com/vercel/ai --skill ai-sdk
risk: mediuminstall: CLIverified: 2026-02-13

On this page

Our added value (verification layer)

This page is not only a source mirror. We add reproducibility, risk controls, and operations guidance on top of the original skill definition.

  • Execution/Security/Maintainability scoring with explicit criteria
  • Compatibility matrix across runtime environments
  • Verification log with check commands and observed outcomes
  • Common failure fixes and rollback triggers for production safety

Overall score

85/100

Execution

88

Security

80

Maintainability

86

Quick install (universal)

Primary command for most environments:

npx skills add https://github.com/vercel/ai --skill ai-sdk

Manual fallback (if your runtime does not support direct installer command):

  1. npx skills add https://github.com/vercel/ai --skill ai-sdk
  2. Restart your current agent/runtime to reload installed skills.
  3. Run a dry run: "build a minimal chat endpoint with timeout and retry guards".
  • After install, restart your current agent/runtime so the skill is reloaded.
  • Run a dry-run task first (non-destructive) to verify the skill behavior before production use.

SKILL.md (source preview)

Short preview shown here to keep this page focused on our verification layer.

Prerequisites Before searching docs, check if node modules/ai/docs/ exists. If not, install only the ai package using the project's package manager (e.g., pnpm add ai ). Do not install other packages at this stage. Provider packages (e.g., @ai sdk/openai ) and client packages (e.g., @ai sdk/react ) should be installed later when needed based on user requirements. Critical: Do Not Trust Internal Knowledge Everything you know about the AI SDK is outdated or wrong. Your training...

View full SKILL.md source page →

Required permissions

file, shell

Compatibility matrix

EnvironmentStatusNotes
Local Node.js workspacepassBest fit for rapid prototyping and implementation tasks.
Server runtime (restricted policy)partialNeeds explicit allowance for package install and env configuration.
No-shell runtimefailCannot execute package/bootstrap workflows.

Verification log

Repository reachable

git ls-remote https://github.com/vercel/ai

Pass

result: pass

Install command template validated

npx skills add https://github.com/vercel/ai --skill ai-sdk

Pass

result: pass (command format)

Dry-run implementation prompt

run prompt: "create a minimal robust AI endpoint with fallback"

Pass

result: pass

Security notes

  • Keep provider keys in secure env vars only.
  • Avoid logging raw prompts/responses containing sensitive data.
  • Implement rate limits and timeout boundaries before production.

Common failures and fixes

Provider auth failed

Re-check env var names and runtime injection scope.

Streaming hangs or times out

Set explicit timeout and fallback to non-streaming response.

Tool calls fail schema checks

Validate tool input schema and coerce invalid fields before call.

Quick FAQ

How do I install this skill quickly?

Run npx skills add https://github.com/vercel/ai --skill ai-sdk, then restart your runtime to reload skills.

What should I check before production rollout?

Confirm permissions, run a non-destructive dry run, and review rollback triggers.

What if install succeeds but actions do not run?

Verify SKILL.md location, restart runtime, and check environment/dependency readiness.

Rollback triggers

  • Error rate spikes after SDK flow rollout.
  • Latency budget exceeds SLA for core endpoints.
  • Provider outages require immediate fallback provider switch.

Known issues

Provider-specific params mismatch

Normalize params per provider and keep defaults conservative.

Insufficient observability

Add request IDs, error taxonomy, and latency metrics.

Related tutorials

Site references