runtime-cache Skill
Vercel Runtime Cache API guidance — ephemeral per-region key-value cache with tag-based invalidation. Shared across Functions, Routing Middleware, and Builds. Use when implementing caching strategies beyond framework-level caching. Published by openai in plugins.
Decision snapshot
Is this a fit?
Deployment, Data analysis, Includes SKILL.md, Reusable instructions
Compatibility not yet detected.
Permission behavior not yet detected.
Copy skill directory
18 days ago
No specific cautions were detected. Review the source and requested permissions before installing.
What is runtime-cache Skill?
Vercel Runtime Cache API guidance — ephemeral per-region key-value cache with tag-based invalidation. Shared across Functions, Routing Middleware, and Builds. Use when implementing caching strategies beyond framework-level caching. Published by openai in plugins. This profile combines repository metadata with install, compatibility, and usage signals so developers can quickly decide whether it fits their agent workflow before opening the source repository.
Automated repository signals based on public metadata such as recency, license, installation evidence, and adoption. These are not a security audit or endorsement. See how SkillIndex evaluates profiles.
Key capabilities
- Includes SKILL.md support
- Reusable instructions support
- Deployment
- Data analysis
- Deployment use cases
- Data analysis use cases
Declared skill metadata
- Source file: plugins/vercel/skills/runtime-cache/SKILL.md
These fields retain source and confidence evidence from the indexed SKILL.md.
Compatibility and setup
- Install or run with Copy skill directory
When to use runtime-cache Skill
- Use it for deployment.
- Use it for data analysis.
Built with
Editorial notes
Source
- Creator: openai
- Repository: openai/plugins
- Skill file: plugins/vercel/skills/runtime-cache/SKILL.md
What it does
Vercel Runtime Cache API guidance — ephemeral per-region key-value cache with tag-based invalidation. Shared across Functions, Routing Middleware, and Builds. Use when implementing caching strategies beyond framework-level caching.
Skill instructions
Vercel Runtime Cache API You are an expert in the Vercel Runtime Cache — an ephemeral caching layer for serverless compute. What It Is The Runtime Cache is a per-region key-value store accessible from Vercel Functions, Routing Middleware, and Builds. It supports tag-based invalidation for granular cache control. - Regional: Each Vercel region has its own isolated cache - Isolated: Scoped per project AND per deployment environment (preview vs production) - Persistent across deployments: Cached data survives new deploys; invalidation via TTL or expireTag - Ephemeral: Fixed storage limit per project; LRU eviction when full - Framework-agnostic: Works with any framework via @vercel/functions Key APIs All APIs from @vercel/functions: Basic Cache Operations ts import { getCache } from '@vercel/functions'; const cache = getCache(); // Store data with TTL and tags await cache.set('user:123', userData, { ttl: 3600, // seconds tags: ['users', 'user:123'], // for bulk invalidation name: 'user-pro
Verified compatibility and discovery
Frequently asked questions
What is runtime-cache?
runtime-cache is a open-source AI agent skill with Copy skill directory. Vercel Runtime Cache API guidance — ephemeral per-region key-value cache with tag-based invalidation. Shared across Functions, Routing Middleware, and Builds.
Who is runtime-cache best for?
runtime-cache is best for reusing agent instructions, scripts, and references, deployment workflows, data analysis workflows.
How do I install runtime-cache?
Install or run runtime-cache using Copy skill directory. Check runtime-cache for the latest setup command.
Is runtime-cache actively maintained?
runtime-cache may need a closer maintenance check before production use.
Project health auto-fetched from the source repository.
Maintain this resource?
Review this source-backed profile, send a correction with evidence, or link to it from your documentation. Claims verify your relationship to the project; profile facts still require source evidence and editorial review.
