ai-infrastructure-hugg…
Hugging Face Inference SDK patterns for TypeScript/Node.js — InferenceClient setup, chat completion, text generation, streaming, embeddings, image generation,…
Pino, Axiom, Sentry installation - one-time project setup for logging and error tracking with source maps upload
$ npx -y skills add agents-inc/skills --skill api-observability-setup-axiom-pino-sentry --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/api-observability-setup-axiom-pino-sentryContext preview
The summary Claude sees to decide when to auto-load this skill.
Pino, Axiom, Sentry installation - one-time project setup for logging and error tracking with source maps upload
name: api-observability-setup-axiom-pino-sentry description: Pino, Axiom, Sentry installation - one-time project setup for logging and error tracking with source maps upload
> **Quick Guide:** One-time project setup for observability. Install `pino`, `next-axiom`, `@sentry/nextjs`. Configure Axiom dataset + Vercel integration. Set up Sentry DSN and config files. Wrap `next.config.ts` with `withAxiom` then `withSentryConfig`. Add `instrumentation.ts` for runtime-specific Sentry init. Source maps are uploaded automatically when `SENTRY_AUTH_TOKEN` is set in CI.
---
**Detailed Resources:**
---
<critical_requirements>
> **All code must follow project conventions in CLAUDE.md** (kebab-case, named exports, import ordering, `import type`, named constants)
**(You MUST create separate Axiom datasets for each environment - development, staging, production)**
**(You MUST configure all three Sentry config files - `sentry.client.config.ts`, `sentry.server.config.ts`, `sentry.edge.config.ts`)**
**(You MUST add source maps upload to CI/CD - Sentry needs source maps for readable stack traces)**
**(You MUST install `pino-pretty` as a devDependency only - never use in production)**
</critical_requirements>
---
**Auto-detection:** pino, next-axiom, @sentry/nextjs, Axiom, Sentry, observability setup, logging setup, error tracking setup, source maps, sentry.client.config, sentry.server.config, sentry.edge.config, withAxiom, withSentryConfig
**When to use:**
**When NOT to use:**
**Key patterns covered:**
---
<philosophy>
**Observability is not optional for production apps.** Without logging and error tracking, debugging production issues becomes guesswork. The Pino + Axiom + Sentry stack provides:
**This skill covers one-time setup only.** For ongoing usage patterns (log levels, structured fields, correlation IDs, alert configuration), use your observability usage skill.
</philosophy>
---
<patterns>
Install all observability packages with correct dependency types.
# Production dependencies npm install pino next-axiom @sentry/nextjs # Development dependencies (pretty printing for local dev) npm install -D pino-pretty
**Why:** `pino-pretty` as devDependency prevents production bundle bloat (~500KB), all core packages are production dependencies for runtime use.
For detailed code examples with good/bad comparisons, see [examples/core.md](examples/core.md#pattern-1-dependency-installation).
---
Create `.env.example` with all required observability variables documented. Group by service, use comments to explain where to get each value, and maintain separate datasets per environment.
Key variables needed:
For complete template with all variables, see [examples/core.md](examples/core.md#pattern-2-environment-variables-template).
---
Wrap Next.js config with `withAxiom` for logging integration, then `withSentryConfig` for source map handling.
Key configuration points:
import { withSentryConfig } from "@sentry/nextjs";
import { withAxiom } from "next-axiom";
const nextConfig = {
/* your config */
};
export default withSentryConfig(withAxiom(nextConfig), {
org: process.env.SENTRY_ORG,
project: process.env.SENTRY_PROJECT,
authToken: process.env.SENTRY_AUTH_TOKEN,
silent: !process.env.CI,
});For complete configuration example, see [examples/core.md](examples/core.md#patt
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,…