ai-infrastructure-hugg…
Hugging Face Inference SDK patterns for TypeScript/Node.js — InferenceClient setup, chat completion, text generation, streaming, embeddings, image generation,…
Turborepo, workspaces, package architecture, @repo/* naming, exports, tree-shaking
$ npx -y skills add agents-inc/skills --skill shared-monorepo-turborepo --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/shared-monorepo-turborepoContext preview
The summary Claude sees to decide when to auto-load this skill.
Turborepo, workspaces, package architecture, @repo/* naming, exports, tree-shaking
name: shared-monorepo-turborepo description: Turborepo, workspaces, package architecture, @repo/* naming, exports, tree-shaking
> **Quick Guide:** Turborepo 2.x for monorepo orchestration. Task pipelines with dependency ordering. Local + remote caching for massive speed gains. Workspaces for package linking. Syncpack for dependency version consistency. Internal packages use `@repo/*` naming, explicit `exports` fields, and `workspace:*` protocol.
---
<critical_requirements>
> **All code must follow project conventions in CLAUDE.md** (kebab-case, named exports, import ordering, `import type`, named constants)
**(You MUST define task dependencies using `dependsOn: ["^build"]` in turbo.json to ensure topological ordering)**
**(You MUST declare all environment variables in the `env` array of turbo.json tasks for proper cache invalidation)**
**(You MUST set `cache: false` for tasks with side effects like dev servers and code generation)**
**(You MUST use `workspace:*` protocol for internal package dependencies)**
**(You MUST use `@repo/*` naming convention for ALL internal packages)**
**(You MUST define explicit `exports` field in package.json - never allow importing internal paths)**
**(You MUST mark React as `peerDependencies` NOT `dependencies` in component packages)**
</critical_requirements>
---
**Auto-detection:** Turborepo configuration, turbo.json, monorepo setup, workspaces, Bun workspaces, syncpack, task pipelines, @repo/\* packages, package.json exports, workspace dependencies, shared configurations
**When to use:**
**When NOT to use:**
**Key patterns covered:**
**Detailed Resources:**
---
<philosophy>
Turborepo is a high-performance build system designed for JavaScript/TypeScript monorepos. It provides intelligent task scheduling, caching, and remote cache sharing to dramatically reduce build times. Combined with workspaces, it enables efficient package management with automatic dependency linking.
</philosophy>
---
<patterns>
Define task dependencies and caching behavior in turbo.json to enable intelligent build orchestration and caching.
{
"tasks": {
"build": {
"dependsOn": ["^build"],
"env": ["DATABASE_URL", "NODE_ENV"],
"outputs": ["dist/**", ".next/**", "!.next/cache/**"]
},
"dev": { "cache": false, "persistent": true }
}
}**Key:** `dependsOn: ["^build"]` ensures topological execution, `env` declares variables for cache invalidation, `cache: false` for side-effect tasks.
See [examples/core.md](examples/core.md) for full good/bad comparison examples.
---
Turborepo's caching system dramatically speeds up builds by reusing previous task outputs when inputs haven't changed.
**Setup:** Link a Vercel account (or self-hosted cache), then set `TURBO_TOKEN` and `TURBO_TEAM` environment variables to enable remote cache sharing.
See [examples/caching.md](examples/caching.md) for remote caching configuration and CI integration examples.
---
Configure workspaces to enable package linking and dependency sharing across monorepo packages.
The official skills marketplace for Agents Inc. 150+ skills covering everything from React and Prisma to Redis, ElevenLabs, and infrastructure tooling. Pick the skills that match your stack and install them via Claude Code. Need more control?
Repo: agents-inc/skills
Hugging Face Inference SDK patterns for TypeScript/Node.js — InferenceClient setup, chat completion, text generation, streaming, embeddings, image generation,…
LiteLLM proxy server setup, TypeScript client patterns via OpenAI SDK, model routing, fallbacks, load balancing, spend tracking, virtual keys, and production…
Serverless GPU compute platform for AI model deployment — web endpoints, GPU functions, model serving, and TypeScript client patterns
Local LLM inference with the Ollama JavaScript client -- chat, streaming, tool calling, vision, embeddings, structured output, model management, and…
Replicate SDK patterns for TypeScript/Node.js -- client setup, predictions, streaming, webhooks, file handling, model versioning, deployments, and training
Together AI SDK patterns for TypeScript — client setup, chat completions, streaming, structured output, function calling, embeddings, image generation,…