Atlas / Skills / jeremylongshore / Langfuse Sdk Patterns

Langfuse Sdk PatternsSAFE

skills/jeremylongshore/langfuse-sdk-patterns

Model-agnostic agent-skills platform with a harness-free canonical layer, verified adapters, and the ccpi package manager. Explore at tonsofskills.com.

Verdict
SAFE
Grade
B
Trust score
89 /100
Version
1.17.0
Hosts
1 documented
License
MIT
Stars
2,824
01

Overview

Model-agnostic agent-skills platform with a harness-free canonical layer, verified adapters, and the ccpi package manager. Explore at tonsofskills.com.

Read from source at commit 4f83675ca38aOBSERVED · 2026-10-09
02

Host compatibility

What the documentation claims. We have not run a compatibility test.

HostStatusNotes
claude-codementioned
03

What it tells the agent

The instruction file, verbatim from the audited commit — this is the text the model reads, and the surface the audit's instruction layer examines. Quoted here so you can judge it without cloning anything.

---
name: langfuse-sdk-patterns
description: 'Langfuse SDK best practices, patterns, and idiomatic usage.

  Use when learning Langfuse SDK patterns, implementing proper tracing,

  or following best practices for LLM observability.

  Trigger with phrases like "langfuse patterns", "langfuse best practices",

  "langfuse SDK guide", "how to use langfuse", "langfuse idioms".

  '
allowed-tools: Read, Write, Edit
version: 1.17.0
license: MIT
author: Jeremy Longshore <[email protected]>
tags:
- saas
- langfuse
- observability
- llm
- tracing
compatibility: Designed for Claude Code
---
# Langfuse SDK Patterns

## Overview

Production-quality patterns for the Langfuse SDK: singleton clients, the `observe` wrapper, `startActiveObservation` for nested traces, session tracking, graceful shutdown, and error-safe tracing.

## Prerequisites

- Completed `langfuse-install-auth` setup
- Understanding of async/await patterns
- For v4+: `@langfuse/tracing`, `@langfuse/otel`, `@opentelemetry/sdk-node`

## Instructions

### Pattern 1: Singleton Client with Graceful Shutdown

```typescript
// src/lib/langfuse.ts -- single file, import everywhere
import { LangfuseClient } from "@langfuse/client";
import { LangfuseSpanProcessor } from "@langfuse/otel";
import { NodeSDK } from "@opentelemetry/sdk-node";

// Singleton client for prompts, datasets, scores
let client: LangfuseClient | null = null;
export function getLangfuseClient(): LangfuseClient {
  if (!client) {
    client = new LangfuseClient();
  }
  return client;
}

// One-time OTel setup (call at app entry point)
let sdk: NodeSDK | null = null;
export function initTracing(): NodeSDK {
  if (!sdk) {
    sdk = new NodeSDK({
      spanProcessors: [new LangfuseSpanProcessor()],
    });
    sdk.start();

    // Graceful shutdown on process exit
    const shutdown = async () => {
      await sdk?.shutdown();
      process.exit(0);
    };
    process.on("SIGTERM", shutdown);
    process.on("SIGINT", shutdown);
  }
  return sdk;
}
```

**Legacy v3 singleton:**

```typescript
import { Langfuse } from "langfuse";

let instance: Langfuse | null = null;

export function getLangfuse(): Langfuse {
  if (!instance) {
    instance = new Langfuse({
      flushAt: 15,
      flushInterval: 10000,
    });
    process.on("beforeExit", () => instance?.shutdownAsync());
  }
  return instance;
}
```

### Pattern 2: `observe` Wrapper for Existing Functions

The `observe` wrapper is the most ergonomic way to add tracing. It wraps any function and auto-creates a span.

```typescript
import { observe, updateActiveObservation } from "@langfuse/tracing";

// Wrap existing functions -- no internal changes needed
const fetchUserProfile = observe(async (userId: string) => {
  updateActiveObservation({ input: { userId } });
  const profile = await db.users.findById(userId);
  updateActiveObservation({ output: { found: !!profile } });
  return profile;
});

// Mark LLM calls as generations
const summarize = observe(
  { name: "summarize-text", asType: "generation" },
  async (text: string) => {
    updateActiveObservation({ model: "gpt-4o-mini", input: text });
    const result = await openai.chat.completions.create({
      model: "gpt-4o-mini",
      messages: [{ role: "user", content: `Summarize: ${text}` }],
    });
    const output = result.choices[0].message.content;
    updateActiveObservation({
      output,
      usage: {
        promptTokens: result.usage?.prompt_tokens,
        completionTokens: result.usage?.completion_tokens,
      },
    });
    return output;
  }
);

// When called inside another observed function, spans auto-nest
const pipeline = observe(async (userId: string) => {
  const profile = await fetchUserProfile(userId);
  const summary = await summarize(profile.bio);
  return { profile, summary };
});
```

### Pattern 3: `startActiveObservation` for Inline Control

Use when you need fine-grained control over observation lifecycle within a function:

```typescript
import { startActiveObservation, updateActiveObservation } from "@langfuse/tracing";

async function processOrder(orderId: string) {
  return await startActiveObservation("process-order", async () => {
    updateActiveObservation({ input: { orderId } });

    // Nested spans are automatic
    const validated = await startActiveObservation("validate", async () => {
      const result = await validateOrder(orderId);
      updateActiveObservation({ output: { valid: result.valid } });
      return result;
    });

    if (!validated.valid) {
      updateActiveObservation({ output: { error: "validation failed" } });
      return { success: false };
    }

    // Generation span for LLM call
    const description = await startActiveObservation(
      { name: "generate-confirmation", asType: "generation" },
      async () => {
        updateActiveObservation({ model: "gpt-4o-mini" });
        const result = await generateConfirmation(orderId);
        updateActiveObservation({ output: result });
        return result;
      }
    );

    updateActiveObservation({ output: { success: true } });
    return { success: true, description };
  });
}
```

### Pattern 4: Session and User Tracking

Link traces across conversation turns for user-level analytics:

```typescript
// v4+: Set session/user via observation metadata
await startActiveObservation("chat-turn", async () => {
  updateActiveObservation({
    metadata: {
      sessionId: "session-abc-123",
      userId: "user-456",
    },
  });
  // All nested observations inherit this context
  await handleUserMessage(message);
});

// v3: Set directly on trace
const trace = langfuse.trace({
  name: "chat-turn",
  sessionId: "session-abc-123", // Groups traces into a session
  userId: "user-456",           // Links to user analytics
  input: { message },
});
```

### Pattern 5: Error-Safe Tracing

Never let tracing failures break your application:

```typescript
import { observe, updateActiveObservation } from "@langfuse/tracing";

const safeObserve = <T ex
04

Trust audit

SAFEgrade B · trust 89/100 Nothing in the source contradicts what it says it does. Grade A is reserved for packages that have also passed the behavioural sandbox.

LayerWhat it checksResult
L0Provenance & inventoryPASS
L1Static analysis of the codePASS
L2Instruction surface (what it tells the agent)PASS
L3Class-specific surfacePASS
L4Behavioural (sandbox)SKIPPED

What the source does

Filesystem
none-observed
Network
none-observed
Shell
none-observed
Dependencies
pinned
Secrets in source
none-found

Findings (0)

No findings outside the package's declared scope.

Gates applied: no_behavioural_pass.

Audited 2026-10-09 · audit v0.4.1 · source sha 4f83675ca38afull audit observations/trust-audit/skill/jeremylongshore__langfuse-sdk-patterns.json · Report an issue / request a re-scan
05

Audit history

Every audit this skill has had.

DateSourceVerdictGradeScoreChange
2026-10-094f83675ca38aSAFEB89first audit
06

Questions

What does the Langfuse Sdk Patterns skill do?

Model-agnostic agent-skills platform with a harness-free canonical layer, verified adapters, and the ccpi package manager. Explore at tonsofskills.com.

Is Langfuse Sdk Patterns safe to install?

The audit found nothing in the source that contradicts what it says it does, and graded it B (89/100). Grade A is held back for packages that have also passed a sandboxed behavioural run, which is why a clean skill reads B.

What can Langfuse Sdk Patterns access on my machine?

The audit observed no filesystem, network or shell use at all in its source.

Which assistants does Langfuse Sdk Patterns work with?

Its documentation mentions claude-code. That is what the text claims, not a compatibility test we ran.

How current is this page?

The grade is for one exact copy of the source (4f83675ca38a), read on 2026-10-09. The repository is watched, and a new audit runs when it changes — this is the first audit.

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