Agent skill

Review Logging Patterns

by activepieces in activepieces/activepieces

Review code for logging patterns and suggest evlog adoption.

MITAuto-check passedAI & LLM Engineering

Install Review Logging Patterns

skills CLI
$ npx skills add activepieces/activepieces --skill review-logging-patterns -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install activepieces/activepieces review-logging-patterns --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/activepieces/activepieces.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/review-logging-patterns .claude/skills/review-logging-patterns && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
review-logging-patterns
GitHub stars
25k
Token cost
~8.2k tokens
SKILL.md length
1,416 words
Files
5 (incl. references)
Skills in repo
13
Repo updated
First seen
Licence
MIT

At a glance

Review code for logging patterns and suggest evlog adoption.

  • Tasks that involve Code review
  • SKILL.md covers When to Use, Quick Reference, Audit logs and Installation, plus 6 more sections
  • Calls npm; reaches in-otel.hyperdx.io; needs AXIOM_API_KEY and HYPERDX_API_KEY
  • Tasks that involve Embeddings

What it does

Review Logging Patterns is an agent skill from activepieces/activepieces. Review code for logging patterns and suggest evlog adoption. Guides setup on Nuxt, Next.js, SvelteKit, Nitro, TanStack Start, React Router, NestJS, Express, Hono, Fastify, Elysia, oRPC, Cloudflare Workers, and standalone TypeScript. Detects console.log spam, unstructured errors, and missing context. Covers wide events, structured errors, drain adapters (Axiom, OTLP, HyperDX, PostHog, Sentry, Better Stack, Datadog), sampling, enrichers, and AI SDK integration (token usage, tool calls, streaming metrics, telemetry…

Its SKILL.md is about 8.2k tokens, which your agent loads only when the skill is triggered. The skill folder holds 5 other files, including reference files (for example `references/code-review.md`, `references/drain-pipeline.md` and `references/structured-errors.md`).

It sits in AI & LLM Engineering, covering Code review, Embeddings and MCP servers. It works with Next.js, Nuxt, SvelteKit and TypeScript. The repository describes itself as: AI Agents & MCPs & AI Workflow Automation • (~400 MCP servers for AI agents) • AI Automation / AI Agent with MCPs • AI Workflows & AI Agents • MCPs for AI Agents. The licence is MIT.

When your agent uses it

  • Tasks that involve Code review
  • Tasks that involve Embeddings
  • Tasks that involve MCP servers

Example prompts

  • “/review-logging-patterns”

Requirements

  • Node.js
  • A credential in AXIOM_API_KEY

What it can do on your machine

Read from SKILL.md and the folder at commit 8656fb8. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • npm

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Hosts in commands or code, which the agent is likely to contact:

    • in-otel.hyperdx.io

    Also links to:

    • evlog.dev

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names these keys or tokens, usually read from environment variables:

    • AXIOM_API_KEY
    • HYPERDX_API_KEY
    • POSTHOG_API_KEY
    • BETTER_STACK_SOURCE_TOKEN
    • DD_API_KEY
    • DATADOG_API_KEY
    • NUXT_AXIOM_API_KEY

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Review Logging Patterns loads about 8.2k tokens when it runs, and up to ~16k if it reads all its reference files. Until then it costs about 148 tokens; SKILL.md has 1,416 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~148
When it runs · the whole SKILL.md, loaded when a task matches
~8.2k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~16k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from activepieces/activepieces at commit 8656fb8, republished under its MIT licence (© activepieces). 1,416 words, ~8,248 tokens.

Download SKILL.mdSave it as .claude/skills/review-logging-patterns/SKILL.md (or your agent's skills folder). This skill also uses 4 other files; get the full folder from GitHub.
name
review-logging-patterns
description
Review code for logging patterns and suggest evlog adoption. Guides setup on Nuxt, Next.js, SvelteKit, Nitro, TanStack Start, React Router, NestJS, Express, Hono, Fastify, Elysia, oRPC, Cloudflare Workers, and standalone TypeScript. Detects console.log spam, unstructured errors, and missing context. Covers wide events, structured errors, drain adapters (Axiom, OTLP, HyperDX, PostHog, Sentry, Better Stack, Datadog), sampling, enrichers, and AI SDK integration (token usage, tool calls, streaming metrics, telemetry integration, cost estimation, embedding metadata).
license
MIT
metadata.author
HugoRCD
metadata.version
0.5

Review logging patterns

Review and improve logging patterns in TypeScript/JavaScript codebases. Transform scattered console.logs into structured wide events and convert generic errors into self-documenting structured errors.

When to Use

  • Setting up evlog in a new or existing project (any supported framework)
  • Reviewing code for logging best practices
  • Converting console.log statements to structured logging
  • Improving error handling with better context
  • Configuring log draining, sampling, or enrichment

Quick Reference

Working on...Resource
Wide events patternsreferences/wide-events.md
Error handlingreferences/structured-errors.md
Code review checklistreferences/code-review.md
Drain pipelinereferences/drain-pipeline.md
Audit logsbuild-audit-logs skill + docs

Audit logs

For security-sensitive actions (auth, billing, admin, data export), use evlog's audit layer — a typed audit field on wide events, not a parallel logger. See the build-audit-logs skill for end-to-end setup (log.audit, withAudit, denials, auditEnricher, auditOnly, signed, mockAudit).

typescript
log.audit({
  action: 'invoice.refund',
  actor: { type: 'user', id: user.id },
  target: { type: 'invoice', id: invoice.id },
  outcome: 'success',
})

Docs: https://www.evlog.dev/use-cases/audit/overview

Installation

bash
npm install evlog

Framework Setup

Nuxt
typescript
// nuxt.config.ts
export default defineNuxtConfig({
  modules: ['evlog/nuxt'],
  evlog: {
    env: { service: 'my-app' },
    include: ['/api/**'],
  },
})

All evlog functions (useLogger, createError, parseError, log) are auto-imported — no import statements needed.

typescript
// server/api/checkout.post.ts — no imports needed
export default defineEventHandler(async (event) => {
  const log = useLogger(event)
  log.set({ user: { id: user.id, plan: user.plan } })
  return { success: true }
})

Drain, enrich, and tail sampling use Nitro hooks in server plugins:

typescript
// server/plugins/evlog-drain.ts
import { createAxiomDrain } from 'evlog/axiom'

export default defineNitroPlugin((nitroApp) => {
  nitroApp.hooks.hook('evlog:drain', createAxiomDrain())
})

Client transport (auto-configured Vue plugin):

typescript
// nuxt.config.ts
evlog: {
  transport: { enabled: true },  // logs sent to /api/_evlog/ingest
}

Client-side: log, setIdentity, clearIdentity are auto-imported in components.

Next.js

Step 1: Create central config — all exports come from here:

typescript
// lib/evlog.ts
import type { DrainContext } from 'evlog'
import { createEvlog } from 'evlog/next'
import { createUserAgentEnricher, createRequestSizeEnricher } from 'evlog/enrichers'
import { createDrainPipeline } from 'evlog/pipeline'

const enrichers = [createUserAgentEnricher(), createRequestSizeEnricher()]
const pipeline = createDrainPipeline<DrainContext>({ batch: { size: 50, intervalMs: 5000 } })
const drain = pipeline(createAxiomDrain({ dataset: 'logs', apiKey: process.env.AXIOM_API_KEY! }))

export const { withEvlog, useLogger, log, createError } = createEvlog({
  service: 'my-app',
  sampling: {
    rates: { info: 10 },
    keep: [{ status: 400 }, { duration: 1000 }],
  },
  routes: {
    '/api/auth/**': { service: 'auth-service' },
    '/api/checkout/**': { service: 'checkout-service' },
  },
  keep: (ctx) => {
    const user = ctx.context.user as { premium?: boolean } | undefined
    if (user?.premium) ctx.shouldKeep = true
  },
  enrich: (ctx) => {
    for (const enricher of enrichers) enricher(ctx)
  },
  drain,
})

Step 2: Wrap route handlers with withEvlog():

typescript
// app/api/checkout/route.ts
import { withEvlog, useLogger } from '@/lib/evlog'

export const POST = withEvlog(async (request: Request) => {
  const log = useLogger()  // Zero arguments — uses AsyncLocalStorage
  log.set({ user: { id: 'user_123', plan: 'enterprise' } })
  log.set({ cart: { items: 3, total: 14999 } })
  return Response.json({ success: true })
})

Step 3: Server Actions — same withEvlog() wrapper:

typescript
// app/actions.ts
'use server'
import { withEvlog, useLogger } from '@/lib/evlog'

export const checkout = withEvlog(async (formData: FormData) => {
  const log = useLogger()
  log.set({ action: 'checkout', source: 'server-action' })
  return { success: true }
})

Step 4: Middleware (optional — sets x-request-id + timing headers):

typescript
// proxy.ts
import { evlogMiddleware } from 'evlog/next'
export const proxy = evlogMiddleware()
export const config = { matcher: ['/api/:path*'] }

Step 5: Client Provider — wrap root layout:

tsx
// app/layout.tsx
import { EvlogProvider } from 'evlog/next/client'

export default function Layout({ children }: { children: React.ReactNode }) {
  return (
    <html lang="en">
      <body>
        <EvlogProvider service="my-app" transport={{ enabled: true, endpoint: '/api/evlog/ingest' }}>
          {children}
        </EvlogProvider>
      </body>
    </html>
  )
}

Step 6: Client logging — in any client component:

tsx
'use client'
import { log, setIdentity, clearIdentity } from 'evlog/next/client'

setIdentity({ userId: 'usr_123' })
log.info({ action: 'checkout_click' })
clearIdentity()

Step 7 (optional): Instrumentation — startup + global onRequestError (SSR/RSC errors outside withEvlog). Use defineNodeInstrumentation(() => import('./lib/evlog')) in root instrumentation.ts to gate Node + cache the import, or write register/onRequestError manually — both are valid. For custom logic, wrap evlog’s register/onRequestError inside lib/evlog.ts (compose with your own init or metrics), then re-export.

Export createInstrumentation() from lib/evlog.ts alongside createEvlog(). See framework docs for coexistence with lockLogger.

Step 8: Client ingest endpoint — receives client logs:

typescript
// app/api/evlog/ingest/route.ts
import { NextRequest } from 'next/server'

const VALID_LEVELS = ['info', 'error', 'warn', 'debug'] as const

export async function POST(request: NextRequest) {
  const origin = request.headers.get('origin')
  const host = request.headers.get('host')
  if (origin && new URL(origin).host !== host) {
    return Response.json({ error: 'Invalid origin' }, { status: 403 })
  }
  const body = await request.json()
  if (!body?.timestamp || !body?.level || !VALID_LEVELS.includes(body.level)) {
    return Response.json({ error: 'Invalid payload' }, { status: 400 })
  }
  const { service: _, ...sanitized } = body
  console.log('[CLIENT LOG]', JSON.stringify({ ...sanitized, service: 'my-app', source: 'client' }))
  return new Response(null, { status: 204 })
}
SvelteKit
typescript
// src/hooks.server.ts
import { initLogger } from 'evlog'
import { createEvlogHooks } from 'evlog/sveltekit'

initLogger({ env: { service: 'my-app' } })

export const { handle, handleError } = createEvlogHooks()

Access the logger via event.locals.log in route handlers or useLogger() from anywhere in the call stack:

typescript
// src/routes/api/users/[id]/+server.ts
import { json } from '@sveltejs/kit'

export const GET = ({ locals, params }) => {
  locals.log.set({ user: { id: params.id } })
  return json({ id: params.id })
}
typescript
import { useLogger } from 'evlog/sveltekit'

async function findUsers() {
  const log = useLogger()
  log.set({ db: { query: 'SELECT * FROM users' } })
}

Full pipeline with drain, enrich, and tail sampling:

typescript
import { createAxiomDrain } from 'evlog/axiom'

export const { handle, handleError } = createEvlogHooks({
  include: ['/api/**'],
  drain: createAxiomDrain(),
  enrich: (ctx) => { ctx.event.region = process.env.FLY_REGION },
  keep: (ctx) => {
    if (ctx.duration && ctx.duration > 2000) ctx.shouldKeep = true
  },
})
Nitro v3
typescript
// nitro.config.ts
import { defineConfig } from 'nitro'
import evlog from 'evlog/nitro/v3'

export default defineConfig({
  modules: [evlog({ env: { service: 'my-api' } })],
})
typescript
// routes/api/checkout.post.ts
import { defineHandler } from 'nitro/h3'
import { useLogger } from 'evlog/nitro/v3'

export default defineHandler(async (event) => {
  const log = useLogger(event)
  log.set({ action: 'checkout' })
  return { ok: true }
})
TanStack Start

TanStack Start uses Nitro v3. Install evlog and add a nitro.config.ts:

typescript
// nitro.config.ts
import { defineConfig } from 'nitro'
import evlog from 'evlog/nitro/v3'

export default defineConfig({
  experimental: { asyncContext: true },
  modules: [evlog({ env: { service: 'my-app' } })],
})

Add the error handling middleware to __root.tsx:

typescript
// src/routes/__root.tsx
import { createMiddleware } from '@tanstack/react-start'
import { evlogErrorHandler } from 'evlog/nitro/v3'

export const Route = createRootRoute({
  server: {
    middleware: [createMiddleware().server(evlogErrorHandler)],
  },
})

Use useRequest() from nitro/context to access the logger:

typescript
import { useRequest } from 'nitro/context'
import type { RequestLogger } from 'evlog'

const req = useRequest()
const log = req.context.log as RequestLogger
log.set({ user: { id: 'user_123' } })
Nitro v2
typescript
// nitro.config.ts
import { defineNitroConfig } from 'nitropack/config'
import evlog from 'evlog/nitro'

export default defineNitroConfig({
  modules: [evlog({ env: { service: 'my-api' } })],
})

Import useLogger from evlog/nitro in routes.

NestJS
typescript
// src/app.module.ts
import { Module } from '@nestjs/common'
import { EvlogModule } from 'evlog/nestjs'

@Module({
  imports: [EvlogModule.forRoot()],
})
export class AppModule {}

EvlogModule.forRoot() registers a global middleware. Use useLogger() to access the request-scoped logger from any controller or service:

typescript
import { useLogger } from 'evlog/nestjs'

async function findUsers() {
  const log = useLogger()
  log.set({ db: { query: 'SELECT * FROM users' } })
}

Full pipeline with drain, enrich, and tail sampling:

typescript
import { createAxiomDrain } from 'evlog/axiom'

EvlogModule.forRoot({
  include: ['/api/**'],
  drain: createAxiomDrain(),
  enrich: (ctx) => { ctx.event.region = process.env.FLY_REGION },
  keep: (ctx) => {
    if (ctx.duration && ctx.duration > 2000) ctx.shouldKeep = true
  },
})

For async configuration with NestJS DI, use forRootAsync():

typescript
EvlogModule.forRootAsync({
  imports: [ConfigModule],
  inject: [ConfigService],
  useFactory: (config) => ({
    drain: createAxiomDrain({ apiKey: config.get('AXIOM_API_KEY') }),
  }),
})
Express
typescript
import express from 'express'
import { initLogger } from 'evlog'
import { evlog, useLogger } from 'evlog/express'

initLogger({ env: { service: 'my-api' } })

const app = express()
app.use(evlog())

app.get('/api/users', (req, res) => {
  req.log.set({ users: { count: 42 } })
  res.json({ users: [] })
})

Use useLogger() to access the logger from anywhere in the call stack without passing req:

typescript
import { useLogger } from 'evlog/express'

async function findUsers() {
  const log = useLogger()
  log.set({ db: { query: 'SELECT * FROM users' } })
}

Full pipeline with drain, enrich, and tail sampling:

typescript
import { createAxiomDrain } from 'evlog/axiom'

app.use(evlog({
  include: ['/api/**'],
  drain: createAxiomDrain(),
  enrich: (ctx) => { ctx.event.region = process.env.FLY_REGION },
  keep: (ctx) => {
    if (ctx.duration && ctx.duration > 2000) ctx.shouldKeep = true
  },
}))
Hono
typescript
import { Hono } from 'hono'
import { initLogger } from 'evlog'
import { evlog, type EvlogVariables } from 'evlog/hono'

initLogger({ env: { service: 'my-api' } })

const app = new Hono<EvlogVariables>()
app.use(evlog())

app.get('/api/users', (c) => {
  const log = c.get('log')
  log.set({ users: { count: 42 } })
  return c.json({ users: [] })
})

Access the logger via c.get('log') in handlers. No useLogger() — use c.get('log') and pass it down explicitly, or use Express/Fastify/Elysia if you need useLogger() across async boundaries.

Structured errors: throw createError(), then in app.onError use parseError() and pass parsed.status as ContentfulStatusCode to c.json() (Hono types the status argument as ContentfulStatusCode, not number).

typescript
import { createError, parseError } from 'evlog'
import type { ContentfulStatusCode } from 'hono/utils/http-status'

app.onError((error, c) => {
  c.get('log').error(error)
  const parsed = parseError(error)
  return c.json(
    { message: parsed.message, why: parsed.why, fix: parsed.fix, link: parsed.link },
    parsed.status as ContentfulStatusCode,
  )
})

Full pipeline with drain, enrich, and tail sampling:

typescript
import { createAxiomDrain } from 'evlog/axiom'

app.use(evlog({
  include: ['/api/**'],
  drain: createAxiomDrain(),
  enrich: (ctx) => { ctx.event.region = process.env.FLY_REGION },
  keep: (ctx) => {
    if (ctx.duration && ctx.duration > 2000) ctx.shouldKeep = true
  },
}))
Fastify
typescript
import Fastify from 'fastify'
import { initLogger } from 'evlog'
import { evlog, useLogger } from 'evlog/fastify'

initLogger({ env: { service: 'my-api' } })

const app = Fastify({ logger: false })
await app.register(evlog)

app.get('/api/users', async (request) => {
  request.log.set({ users: { count: 42 } })
  return { users: [] }
})

request.log is the evlog wide-event logger (shadows Fastify's built-in pino logger on the request). Fastify's pino logger remains accessible via fastify.log.

Use useLogger() to access the logger from anywhere in the call stack without passing request:

typescript
import { useLogger } from 'evlog/fastify'

async function findUsers() {
  const log = useLogger()
  log.set({ db: { query: 'SELECT * FROM users' } })
}

Full pipeline with drain, enrich, and tail sampling:

typescript
import { createAxiomDrain } from 'evlog/axiom'

await app.register(evlog, {
  include: ['/api/**'],
  drain: createAxiomDrain(),
  enrich: (ctx) => { ctx.event.region = process.env.FLY_REGION },
  keep: (ctx) => {
    if (ctx.duration && ctx.duration > 2000) ctx.shouldKeep = true
  },
})
Elysia
typescript
import { Elysia } from 'elysia'
import { initLogger } from 'evlog'
import { evlog, useLogger } from 'evlog/elysia'

initLogger({ env: { service: 'my-api' } })

const app = new Elysia()
  .use(evlog())
  .get('/api/users', ({ log }) => {
    log.set({ users: { count: 42 } })
    return { users: [] }
  })
  .listen(3000)

Use useLogger() to access the logger from anywhere in the call stack:

typescript
import { useLogger } from 'evlog/elysia'

async function findUsers() {
  const log = useLogger()
  log.set({ db: { query: 'SELECT * FROM users' } })
}

Full pipeline with drain, enrich, and tail sampling:

typescript
import { createAxiomDrain } from 'evlog/axiom'

app.use(evlog({
  include: ['/api/**'],
  drain: createAxiomDrain(),
  enrich: (ctx) => { ctx.event.region = process.env.FLY_REGION },
  keep: (ctx) => {
    if (ctx.duration && ctx.duration > 2000) ctx.shouldKeep = true
  },
}))
React Router
typescript
// react-router.config.ts
import type { Config } from '@react-router/dev/config'

export default {
  future: {
    v8_middleware: true,
  },
} satisfies Config
typescript
// app/root.tsx
import { initLogger } from 'evlog'
import { evlog } from 'evlog/react-router'

initLogger({ env: { service: 'my-api' } })

export const middleware: Route.MiddlewareFunction[] = [
  evlog(),
]

Access the logger via context.get(loggerContext) in loaders and actions:

typescript
// app/routes/api.users.$id.tsx
import { loggerContext } from 'evlog/react-router'

export async function loader({ params, context }: Route.LoaderArgs) {
  const log = context.get(loggerContext)
  log.set({ user: { id: params.id } })
  return { users: [] }
}

Use useLogger() to access the logger from anywhere in the call stack without passing context:

typescript
import { useLogger } from 'evlog/react-router'

async function findUsers() {
  const log = useLogger()
  log.set({ db: { query: 'SELECT * FROM users' } })
}

Full pipeline with drain, enrich, and tail sampling:

typescript
import { createAxiomDrain } from 'evlog/axiom'

export const middleware: Route.MiddlewareFunction[] = [
  evlog({
    include: ['/api/**'],
    drain: createAxiomDrain(),
    enrich: (ctx) => { ctx.event.region = process.env.FLY_REGION },
    keep: (ctx) => {
      if (ctx.duration && ctx.duration > 2000) ctx.shouldKeep = true
    },
  }),
]
oRPC
typescript
import { os } from '@orpc/server'
import { RPCHandler } from '@orpc/server/fetch'
import { initLogger } from 'evlog'
import { evlog, withEvlog, type EvlogOrpcContext } from 'evlog/orpc'

initLogger({ env: { service: 'my-rpc' } })

const base = os.$context<EvlogOrpcContext>().use(evlog())

const router = {
  ping: base.handler(({ context }) => {
    context.log.set({ pinged: true })
    return { ok: true }
  }),
}

const handler = withEvlog(new RPCHandler(router))

export default async function fetch(request: Request) {
  const { matched, response } = await handler.handle(request, { prefix: '/rpc' })
  return matched ? response : new Response('Not Found', { status: 404 })
}

withEvlog() wraps the handler so each matched request emits one wide event; os.use(evlog()) exposes context.log on every procedure that descends from base and tags the wide event with operation (the procedure path joined with .).

Use useLogger() to access the logger from utility modules:

typescript
import { useLogger } from 'evlog/orpc'

async function chargeCard(amount: number) {
  const log = useLogger()
  log.set({ payment: { amount } })
}

Full pipeline with drain, enrich, and tail sampling:

typescript
import { createAxiomDrain } from 'evlog/axiom'

const handler = withEvlog(new RPCHandler(router), {
  include: ['/rpc/**'],
  drain: createAxiomDrain(),
  enrich: (ctx) => { ctx.event.region = process.env.FLY_REGION },
  keep: (ctx) => {
    if (ctx.duration && ctx.duration > 2000) ctx.shouldKeep = true
  },
})
Cloudflare Workers
typescript
import { initWorkersLogger, createWorkersLogger } from 'evlog/workers'

initWorkersLogger({ env: { service: 'edge-api' } })

export default {
  async fetch(request: Request) {
    const log = createWorkersLogger(request)
    try {
      log.set({ route: 'health' })
      const response = new Response('ok', { status: 200 })
      log.emit({ status: response.status })
      return response
    } catch (error) {
      log.error(error as Error)
      log.emit({ status: 500 })
      throw error
    }
  },
}
Vite Plugin (any Vite-based framework)

For any Vite-based project (SvelteKit, Astro, SolidStart, React+Vite, etc.), use the Vite plugin for auto-init, auto-imports, and build-time features:

typescript
// vite.config.ts
import evlog from 'evlog/vite'

export default defineConfig({
  plugins: [
    evlog({
      service: 'my-app',
      autoImports: true,           // auto-import log, createEvlogError, parseError
      strip: ['debug'],            // remove log.debug() in production
      sourceLocation: true,        // inject file:line in dev + prod
      client: {                    // client-side logging
        transport: { endpoint: '/api/logs' },
      },
    }),
  ],
})

Server-side middleware (drain, enrich, keep, routes) is still configured in the framework integration (e.g., evlog() middleware for Hono/Express/SvelteKit). The Vite plugin handles build-time DX only.

Standalone TypeScript
typescript
import { initLogger, createRequestLogger } from 'evlog'

initLogger({ env: { service: 'my-worker', environment: 'production' } })

const log = createRequestLogger({ jobId: job.id })
log.set({ source: job.source, recordsSynced: 150 })
log.emit()  // Manual emit required in standalone

Configuration Options

All options work in Nuxt (evlog key), Nitro (passed to evlog()), Next.js (createEvlog()), and standalone (initLogger()).

OptionTypeDefaultDescription
env.service / servicestring'app'Service name in logs
enabledbooleantrueGlobal toggle (no-ops when false)
prettybooleantrue in devPretty tree format vs JSON
silentbooleanfalseSuppress console output. Events still go to drains
includestring[]All routesRoute glob patterns to log
excludestring[]NoneRoute patterns to exclude (takes precedence)
routesRecord<string, { service }>--Route-specific service names
minLevel'debug' | 'info' | 'warn' | 'error''debug'Hard threshold for the global log API and client log (not request wide events). Use sampling.rates for probabilistic volume on requests
sampling.ratesobject--Head sampling: { info: 10, warn: 50 } (0-100%)
sampling.keeparray--Tail sampling: [{ status: 400 }, { duration: 1000 }]
drain(ctx) => void--Drain callback (Next.js, standalone)
enrich(ctx) => void--Enrich callback (Next.js)
keep(ctx) => void--Custom tail sampling callback (Next.js)
redactboolean | RedactConfigtrue in productionEnabled by default in production. false to disable. Object for fine-grained control
Show full SKILL.md (577 more words)Show less
Nitro Hooks (Nuxt, Nitro v2/v3)
HookWhenUse
evlog:drainAfter enrichmentSend events to external services
evlog:enrichAfter emit, before drainAdd derived context
evlog:emit:keepDuring emitCustom tail sampling logic
closeServer shutdownFlush drain pipeline buffers

Drain Adapters

AdapterImportEnv Vars
Axiomevlog/axiomAXIOM_API_KEY, AXIOM_DATASET
OTLPevlog/otlpOTLP_ENDPOINT (or OTEL_EXPORTER_OTLP_ENDPOINT)
HyperDXevlog/hyperdxHYPERDX_API_KEY (optional HYPERDX_OTLP_ENDPOINT; defaults to https://in-otel.hyperdx.io)
PostHogevlog/posthogPOSTHOG_API_KEY, POSTHOG_HOST
Sentryevlog/sentrySENTRY_DSN
Better Stackevlog/better-stackBETTER_STACK_SOURCE_TOKEN
Datadogevlog/datadogDD_API_KEY or DATADOG_API_KEY, optional DD_SITE / DATADOG_LOGS_URL
File Systemevlog/fsNone (local file system)
HTTP (browser ingest)evlog/httpNone (configure endpoint in code). evlog/browser is deprecated; same API, removed next major

In Nuxt/Nitro, use the NUXT_ prefix (e.g., NUXT_AXIOM_API_KEY) so values are available via useRuntimeConfig(). All adapters also read unprefixed variables as fallback.

Setup pattern per framework:

typescript
// Nuxt/Nitro: server/plugins/evlog-drain.ts
import { createAxiomDrain } from 'evlog/axiom'
export default defineNitroPlugin((nitroApp) => {
  nitroApp.hooks.hook('evlog:drain', createAxiomDrain())
})

// Hono / Express / Elysia: pass drain in middleware options
import { createAxiomDrain } from 'evlog/axiom'
app.use(evlog({ drain: createAxiomDrain() }))

// Fastify: pass drain in plugin options
import { createAxiomDrain } from 'evlog/axiom'
await app.register(evlog, { drain: createAxiomDrain() })

// NestJS: pass drain in module options
import { createAxiomDrain } from 'evlog/axiom'
EvlogModule.forRoot({ drain: createAxiomDrain() })

// Next.js: pass drain to createEvlog()
import { createAxiomDrain } from 'evlog/axiom'
import { createDrainPipeline } from 'evlog/pipeline'
const pipeline = createDrainPipeline<DrainContext>({ batch: { size: 50 } })
const drain = pipeline(createAxiomDrain())
// then: createEvlog({ ..., drain })

// Standalone: pass drain to initLogger()
initLogger({ env: { service: 'my-app' }, drain: createAxiomDrain() })

See references/drain-pipeline.md for batching, retry, and buffer overflow config.


Enrichers

Built-in: createUserAgentEnricher(), createGeoEnricher(), createRequestSizeEnricher(), createTraceContextEnricher() — all from evlog/enrichers.

typescript
// Nuxt/Nitro: server/plugins/evlog-enrich.ts
import { createUserAgentEnricher, createGeoEnricher } from 'evlog/enrichers'
export default defineNitroPlugin((nitroApp) => {
  const enrichers = [createUserAgentEnricher(), createGeoEnricher()]
  nitroApp.hooks.hook('evlog:enrich', (ctx) => {
    for (const enricher of enrichers) enricher(ctx)
  })
})

// Next.js: in lib/evlog.ts
createEvlog({
  enrich: (ctx) => {
    for (const enricher of enrichers) enricher(ctx)
    ctx.event.region = process.env.VERCEL_REGION
  },
})

Auto-Redaction (PII Protection)

Built-in redaction scrubs sensitive data from wide events before console output and before any drain sees the data. Enabled by default in production (NODE_ENV === 'production'), disabled in development. Uses smart partial masking — preserving enough context for debugging.

typescript
// Disable in production (opt-out)
evlog: { redact: false }

// Add custom paths on top of built-ins
evlog: {
  redact: {
    paths: ['user.password', 'headers.authorization'],
  }
}

// Only specific built-ins
evlog: {
  redact: {
    builtins: ['email', 'creditCard'],
  }
}

// No built-ins, only custom (uses flat [REDACTED] replacement)
evlog: {
  redact: {
    builtins: false,
    paths: ['user.ssn'],
    patterns: [/SECRET_\w+/g],
  }
}

Built-in patterns with smart masking output:

PatternExample InputMasked Output
creditCard4111111111111111****1111
emailalice@example.coma***@***.com
ipv4192.168.1.100***.***.***.100
phone+33 6 12 34 56 78+33 ****5678
jwteyJhbGciOi...eyJ***.***
bearerBearer sk_live_abc...Bearer ***
ibanFR76 3000 6000 ...189FR76****189

Works in all frameworks: Nuxt (evlog config), Nitro (evlog() module options), Next.js (createEvlog()), standalone (initLogger()), and all middleware integrations (Hono, Express, Fastify, Elysia, NestJS).


AI SDK Integration

Capture token usage, tool calls, model info, streaming metrics, tool execution timing, cost estimation, and embedding metadata from the Vercel AI SDK into wide events. Import from evlog/ai. Requires ai >= 6.0.0 as a peer dependency.

Basic setup (middleware)
typescript
import { createAILogger } from 'evlog/ai'

const log = useLogger(event) // or any RequestLogger
const ai = createAILogger(log)

const result = streamText({
  model: ai.wrap('anthropic/claude-sonnet-4.6'),  // accepts string or model object
  messages,
})

ai.wrap() uses model middleware to transparently capture all LLM calls. Works with generateText, streamText, and ToolLoopAgent.

Telemetry integration (deeper observability)

For tool execution timing, success/failure tracking, and total generation wall time, add createEvlogIntegration():

typescript
import { createAILogger, createEvlogIntegration } from 'evlog/ai'

const ai = createAILogger(log)

const agent = new ToolLoopAgent({
  model: ai.wrap('anthropic/claude-sonnet-4.6'),
  tools: { searchWeb, queryDatabase },
  stopWhen: stepCountIs(5),
  experimental_telemetry: {
    isEnabled: true,
    integrations: [createEvlogIntegration(ai)],
  },
})

This adds ai.tools (per-tool { name, durationMs, success, error? }) and ai.totalDurationMs to the wide event.

Embeddings
typescript
const { embedding, usage } = await embed({ model: embeddingModel, value: query })
ai.captureEmbed({ usage, model: 'text-embedding-3-small', dimensions: 1536 })

For embedMany, pass the batch count:

typescript
ai.captureEmbed({ usage, model: 'text-embedding-3-small', count: documents.length })
Cost estimation

Pass a pricing map to get ai.estimatedCost in the wide event:

typescript
const ai = createAILogger(log, {
  cost: {
    'claude-sonnet-4.6': { input: 3, output: 15 },
    'gpt-4o': { input: 2.5, output: 10 },
  },
})
Wide event ai field

Includes: calls, model, provider, inputTokens, outputTokens, totalTokens, cacheReadTokens, reasoningTokens, finishReason, toolCalls, steps, msToFirstChunk, msToFinish, tokensPerSecond, error, tools (via telemetry integration), totalDurationMs (via telemetry integration), embedding (via captureEmbed), estimatedCost (via cost option).

Anti-patterns to detect:

Anti-PatternFix
Manual token tracking in onFinishai.wrap() — middleware captures automatically
console.log('tokens:', result.usage)ai.wrap() — structured ai.* fields in wide event
No AI observabilityAdd createAILogger(log) + ai.wrap()
No tool execution timingAdd createEvlogIntegration(ai) to experimental_telemetry.integrations
Manual cost calculationUse cost option in createAILogger()

Structured Errors

typescript
import { createError } from 'evlog'  // or auto-imported in Nuxt

// Minimal
throw createError({ message: 'Database connection failed', status: 500 })

// Standard
throw createError({ message: 'Payment failed', status: 402, why: 'Card declined by issuer' })

// Complete
throw createError({
  message: 'Payment failed',
  status: 402,
  why: 'Card declined by issuer - insufficient funds',
  fix: 'Please use a different payment method or contact your bank',
  link: 'https://docs.example.com/payments/declined',
  cause: originalError,
})

// Backend-only context (wide events / drains — never HTTP body or parseError())
throw createError({
  message: 'Not allowed',
  status: 403,
  why: 'Insufficient permissions',
  internal: { correlationId: 'req_abc', resourceId: 'proj_123' },
})

Frontend — extract user-facing fields with parseError() (internal is never returned to clients):

typescript
import { parseError } from 'evlog'

const error = parseError(err)
// error.message, error.status, error.why, error.fix, error.link

See references/structured-errors.md for common patterns and templates.


Anti-Patterns to Detect

Anti-PatternFix
Multiple console.log in one functionSingle wide event with log.set()
throw new Error('...')throw createError({ message, status, why, fix })
console.error(e); throw elog.error(e); throw createError(...)
No logging in request handlersAdd useLogger(event) / useLogger() / createRequestLogger()
Flat log data { uid, n, t }Grouped objects: { user: {...}, cart: {...} }
Logging sensitive data log.set({ user: body })Explicit fields: { user: { id: body.id, plan: body.plan } } + enable redact: true
Putting support-only IDs in why / messageUse createError({ ..., internal: { ... } }) for non-user-facing diagnostics

See references/code-review.md for the full checklist.


Loading Reference Files

Load based on what you're working on — do not load all at once:

© activepieces, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 4 other files (references) in .agents/skills/review-logging-patterns of activepieces/activepieces.

  • SKILL.md
  • references/code-review.md
  • references/drain-pipeline.md
  • references/structured-errors.md
  • references/wide-events.md

Open the folder on GitHubat commit 8656fb8

Compare with similar skills

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Review Logging Patternsevloghq/evlog1.9k—~11kAutomated safety check: PassMIT
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AI SDKvercel-labs/ai-facts16821 repos~1.2kAutomated safety check: PassNone
Neurolink Guidejuspay/neurolink143—~1.4kAutomated safety check: PassMIT

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Questions about Review Logging Patterns

What does Review Logging Patterns do?

Review code for logging patterns and suggest evlog adoption. Review Logging Patterns is an agent skill from activepieces/activepieces. Review code for logging patterns and suggest evlog adoption.

When should I use Review Logging Patterns?

Review Logging Patterns fits situations like: tasks that involve Code review; tasks that involve Embeddings; tasks that involve MCP servers.

How do I install Review Logging Patterns in Claude Code?

Run `npx skills add activepieces/activepieces --skill review-logging-patterns -a claude-code`. Or copy the skill folder (.agents/skills/review-logging-patterns in activepieces/activepieces) into .claude/skills/review-logging-patterns in your project. Claude Code loads it when a task matches its description.

How do I install Review Logging Patterns in Codex?

Run `npx skills add activepieces/activepieces --skill review-logging-patterns -a codex`. Or copy the skill folder (.agents/skills/review-logging-patterns in activepieces/activepieces) into .agents/skills/review-logging-patterns in your project. Codex loads it when a task matches its description.

Can I use Review Logging Patterns in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add activepieces/activepieces --skill review-logging-patterns -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/review-logging-patterns, .gemini/skills/review-logging-patterns, .github/skills/review-logging-patterns and .opencode/skills/review-logging-patterns in your project.

What does Review Logging Patterns need to run?

Going by SKILL.md and its folder, Review Logging Patterns needs the command-line tools its instructions call (npm) and credentials named AXIOM_API_KEY, HYPERDX_API_KEY, POSTHOG_API_KEY and BETTER_STACK_SOURCE_TOKEN. Our summary lists: Node.js; A credential in AXIOM_API_KEY.

Does Review Logging Patterns access the network?

SKILL.md names 2 domains. In commands or code: in-otel.hyperdx.io; the agent is likely to contact it when it follows the instructions. As links in the text: evlog.dev. This is read from the text; nothing was executed.

Is Review Logging Patterns safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Review Logging Patterns use?

Review Logging Patterns is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Review Logging Patterns use?

About 8.2k tokens (SKILL.md is roughly 33k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 8.2k tokens, read only when the agent opens those files.

What are the alternatives to Review Logging Patterns?

Skills that share tags, products or a category with Review Logging Patterns: Better Auth (secondsky/claude-skills, 227 stars), Review Logging Patterns (evloghq/evlog, 1.9k stars), Cloudflare Workers Frameworks (secondsky/claude-skills, 227 stars) and AI SDK (vercel-labs/ai-facts, 168 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Review Logging Patterns?

activepieces (a GitHub organization) maintains it in activepieces/activepieces, which has 24,941 GitHub stars. The repository holds 13 skills in this directory. The repository was last updated on October 8, 2026.

Source: activepieces/activepieces on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.