New: 98,000+ skills indexed from GitHub repos with 100+ stars · every skill safety-checkedBrowse top skillsTop skills
Esc to closeBrowse all skills
Submit a skillBrowse skills
Submit a skillBrowse skills

Agent skill

Langfuse Install Auth

by jeremylongshore in jeremylongshore/tons-of-skills-marketplace

Install and configure Langfuse SDK authentication for LLM observability.

MITAuto-check: notesAI & LLM Engineering

Install Langfuse Install Auth

skills CLI
$ npx skills add jeremylongshore/tons-of-skills-marketplace --skill langfuse-install-auth -a claude-code

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

GitHub CLI
$ gh skill install jeremylongshore/tons-of-skills-marketplace langfuse-install-auth --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/jeremylongshore/tons-of-skills-marketplace.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/.curated/langfuse-install-auth .claude/skills/langfuse-install-auth && 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
langfuse-install-auth
GitHub stars
2.8k
Token cost
~1.7k tokens
SKILL.md length
374 words
Files
1
Skills in repo
3,342
Repo updated
First seen
Licence
MIT

At a glance

Install and configure Langfuse SDK authentication for LLM observability.

  • Works in 6 steps: Install SDK → Get API Keys → Configure Environment Variables → …
  • Setting up a new Langfuse integration
  • SKILL.md covers Overview, Prerequisites, Instructions and SDK Version Comparison, plus 5 more sections
  • Calls npm and pip; reaches cloud.langfuse.com; needs LANGFUSE_PUBLIC_KEY and LANGFUSE_SECRET_KEY

What it does

Langfuse Install Auth is an agent skill from jeremylongshore/tons-of-skills-marketplace. Install and configure Langfuse SDK authentication for LLM observability. Use when setting up a new Langfuse integration, configuring API keys, or initializing Langfuse tracing in your project. Trigger with phrases like "install langfuse", "setup langfuse", "langfuse auth", "configure langfuse API key", "langfuse tracing setup".

Its SKILL.md is about 1.7k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts. Compatibility notes: Designed for Claude Code

It sits in AI & LLM Engineering, covering LLM observability. It works with Langfuse, Python and OpenTelemetry. The repository describes itself as: Model-agnostic agent-skills platform with a harness-free canonical layer, verified adapters, and the ccpi package manager. Explore at tonsofskills.com. The licence is MIT.

When your agent uses it

  • Setting up a new Langfuse integration
  • Configuring API keys
  • Initializing Langfuse tracing in your project
  • With phrases like install langfuse

Example prompts

  • “install langfuse”
  • “setup langfuse”
  • “langfuse auth”
  • “/langfuse-install-auth”

Requirements

  • Python 3
  • Node.js
  • A credential in LANGFUSE_PUBLIC_KEY
  • A credential in LANGFUSE_SECRET_KEY
  • Compatibility (from SKILL.md): Designed for Claude Code
  • Pre-approved tools (allowed-tools): Read, Write, Edit, Bash(npm:*), Bash(pip:*), Bash(pnpm:*), Grep

Workflow steps

6 steps, taken from the step headings in SKILL.md.

  1. Install SDK
  2. Get API Keys
  3. Configure Environment Variables
  4. Initialize and Verify (v4+ Modular SDK)
  5. Initialize and Verify (v3 Legacy SDK)
  6. Python Verification

What it can do on your machine

Read from SKILL.md and the folder at commit cfae287. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves these tools, so the agent can use them without asking each time:

    • Read
    • Write
    • Edit
    • Bash(npm:*)
    • Bash(pip:*)
    • Bash(pnpm:*)
    • Grep

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • npm
    • pip

    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:

    • cloud.langfuse.com

    Also links to:

    • langfuse.com

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

  • Credentials

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

    • LANGFUSE_PUBLIC_KEY
    • LANGFUSE_SECRET_KEY

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

  • Compatibility

    Designed for Claude Code

    From compatibility in the SKILL.md frontmatter.

Context cost

Langfuse Install Auth loads about 1.7k tokens when it runs. Until then it costs about 88 tokens; SKILL.md has 374 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~88
When it runs · the whole SKILL.md, loaded when a task matches
~1.7k

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: notes

The automated check noted patterns worth knowing about, such as sudo or a known installer.

  • NoteMentions a .env fileSKILL.md:90
    # Or create .env file
  • NoteMentions a .env fileSKILL.md:91
    cat >> .env << 'EOF'

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 jeremylongshore/tons-of-skills-marketplace at commit cfae287, republished under its MIT licence (© jeremylongshore). 374 words, ~1,688 tokens.

Download SKILL.mdSave it as .claude/skills/langfuse-install-auth/SKILL.md (or your agent's skills folder).
name
langfuse-install-auth
description
Install and configure Langfuse SDK authentication for LLM observability. Use when setting up a new Langfuse integration, configuring API keys, or initializing Langfuse tracing in your project. Trigger with phrases like "install langfuse", "setup langfuse", "langfuse auth", "configure langfuse API key", "langfuse tracing setup".
allowed-tools
Read, Write, Edit, Bash(npm:*), Bash(pip:*), Bash(pnpm:*), Grep
compatibility
Designed for Claude Code
version
1.17.0
license
MIT
author
Jeremy Longshore <jeremy@intentsolutions.io>
tags
saas, langfuse, api, observability, llm

Langfuse Install & Auth

Overview

Install the Langfuse SDK and configure authentication for LLM observability. Covers both the legacy langfuse package (v3) and the modern modular SDK (v4+/v5) built on OpenTelemetry.

Prerequisites

  • Node.js 18+ or Python 3.9+
  • Package manager (npm, pnpm, or pip)
  • Langfuse account (cloud at https://cloud.langfuse.com or self-hosted)
  • Public Key (pk-lf-...) and Secret Key (sk-lf-...) from project settings

Instructions

Step 1: Install SDK

TypeScript/JavaScript (v4+ modular SDK -- recommended):

bash
set -euo pipefail
# Core client for prompt management, datasets, scores
npm install @langfuse/client

# Tracing (observe, startActiveObservation)
npm install @langfuse/tracing @langfuse/otel @opentelemetry/sdk-node

# OpenAI integration (drop-in wrapper)
npm install @langfuse/openai

# LangChain integration
npm install @langfuse/langchain

TypeScript/JavaScript (v3 legacy -- single package):

bash
npm install langfuse

Python:

bash
pip install langfuse
Step 2: Get API Keys
  1. Open Langfuse dashboard (https://cloud.langfuse.com or your self-hosted URL)
  2. Go to Settings > API Keys
  3. Click Create new API key pair
  4. Copy both keys:
    • Public Key: pk-lf-... (identifies your project)
    • Secret Key: sk-lf-... (grants write access -- keep secret)
  5. Note the host URL (cloud default: https://cloud.langfuse.com)
Step 3: Configure Environment Variables
bash
# Set environment variables
export LANGFUSE_PUBLIC_KEY="pk-lf-..."
export LANGFUSE_SECRET_KEY="sk-lf-..."
export LANGFUSE_BASE_URL="https://cloud.langfuse.com"

# Or create .env file
cat >> .env << 'EOF'
LANGFUSE_PUBLIC_KEY=pk-lf-your-public-key
LANGFUSE_SECRET_KEY=sk-lf-your-secret-key
LANGFUSE_BASE_URL=https://cloud.langfuse.com
EOF

Note: v4+ uses LANGFUSE_BASE_URL. Legacy v3 uses LANGFUSE_HOST or LANGFUSE_BASEURL.

Step 4: Initialize and Verify (v4+ Modular SDK)
typescript
// src/lib/langfuse.ts
import { LangfuseClient } from "@langfuse/client";
import { startActiveObservation } from "@langfuse/tracing";
import { LangfuseSpanProcessor } from "@langfuse/otel";
import { NodeSDK } from "@opentelemetry/sdk-node";

// 1. Register the OpenTelemetry span processor (once at app startup)
const sdk = new NodeSDK({
  spanProcessors: [new LangfuseSpanProcessor()],
});
sdk.start();

// 2. Create the Langfuse client for prompt/dataset/score operations
export const langfuse = new LangfuseClient({
  publicKey: process.env.LANGFUSE_PUBLIC_KEY,
  secretKey: process.env.LANGFUSE_SECRET_KEY,
  baseUrl: process.env.LANGFUSE_BASE_URL,
});

// 3. Verify connection
async function verify() {
  await startActiveObservation("connection-test", async (span) => {
    span.update({ input: { test: true } });
    span.update({ output: { status: "connected" } });
  });
  console.log("Langfuse connection verified. Check dashboard for trace.");
}

verify();
Step 5: Initialize and Verify (v3 Legacy SDK)
typescript
import { Langfuse } from "langfuse";

const langfuse = new Langfuse({
  publicKey: process.env.LANGFUSE_PUBLIC_KEY,
  secretKey: process.env.LANGFUSE_SECRET_KEY,
  baseUrl: process.env.LANGFUSE_HOST,
});

// Verify with a test trace
const trace = langfuse.trace({
  name: "connection-test",
  metadata: { test: true },
});

await langfuse.flushAsync();
console.log("Connected. Trace URL:", trace.getTraceUrl());

// Clean shutdown
process.on("beforeExit", async () => {
  await langfuse.shutdownAsync();
});
Step 6: Python Verification
python
from langfuse import Langfuse
import os

langfuse = Langfuse(
    public_key=os.environ["LANGFUSE_PUBLIC_KEY"],
    secret_key=os.environ["LANGFUSE_SECRET_KEY"],
    host=os.environ.get("LANGFUSE_HOST", "https://cloud.langfuse.com"),
)

# Test trace
trace = langfuse.trace(name="connection-test", metadata={"test": True})
langfuse.flush()
print(f"Connected. Trace: {trace.get_trace_url()}")

SDK Version Comparison

Featurev3 (langfuse)v4+ (@langfuse/*)
PackageSingle langfuseModular: @langfuse/client, @langfuse/tracing, @langfuse/otel
Base URL env varLANGFUSE_HOSTLANGFUSE_BASE_URL
Tracinglangfuse.trace()startActiveObservation() / observe()
Client classLangfuseLangfuseClient
OpenAI wrapperobserveOpenAI() from langfuseobserveOpenAI() from @langfuse/openai
FoundationCustomOpenTelemetry
Show full SKILL.md (171 more words)Show less

Error Handling

ErrorCauseSolution
401 UnauthorizedInvalid or expired API keyRe-check keys in Langfuse dashboard Settings > API Keys
ECONNREFUSEDWrong host URL or server downVerify LANGFUSE_BASE_URL / LANGFUSE_HOST
Missing required configurationEnv vars not loadedEnsure dotenv/config imported at entry point
Module not foundPackage not installedRun npm install or pip install again
Using pk- key as secretKeys swappedPublic key starts pk-lf-, secret starts sk-lf-

Output

Produce a connection-verification receipt with SDK version, configured host, project identifier, and a trace URL or identifier. Record only whether each credential is set; never print key values, headers, or compiled prompts.

Examples

Configure the v4 SDK with environment-provided keys, submit a single synthetic trace, and confirm it appears in the intended project. For a self-hosted host change, verify the health endpoint and test trace before removing the previous host configuration.

Resources

Next Steps

After auth is working, proceed to langfuse-hello-world for your first traced LLM call.

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

Files

Just SKILL.md in skills/.curated/langfuse-install-auth of jeremylongshore/tons-of-skills-marketplace.

Open the folder on GitHubat commit cfae287

Compare with similar skills

Langfuse Install Auth next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Langfuse Install Auth compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Langfuse Install Auth this skilljeremylongshore/tons-of-skills-marketplace2.8k—~1.7kAutomated safety check: NotesMIT
Agentsop Observability Setupagentsope/SkillAlchemy436—~4.4kAutomated safety check: PassMIT
Phoenix Integration SnippetsArize-ai/phoenix12k—~1.4kAutomated safety check: PassApache-2.0
Phoenix Release PleaseArize-ai/phoenix12k—~708Automated safety check: PassApache-2.0
Olore Langfuse Latestolorehq/olore104—~1.2kAutomated safety check: PassMIT
Telemetry AnalyzerIBM/ibm-watsonx-orchestrate-adk178—~10kAutomated safety check: NotesMIT

Similar skills

  • Agentsop Observability Setup

    agentsope/SkillAlchemy

    Enhancement-overlay skill — the DECISION + WIRING layer for LM observability that the single-backend skills [[langsmith]], [[phoenix]], [[mlflow]] do NOT cover.

    436 GitHub stars~4.4k tokensUpdated 2 days ago
    AI & LLM EngineeringAuto-check passed

  • Phoenix Integration Snippets

    Arize-ai/phoenix

    Generates onboarding code snippets for Phoenix tracing integrations and wires them into the project onboarding UI.

    12k GitHub stars~1.4k tokensUpdated yesterday
    AI & LLM EngineeringAuto-check passed

  • Phoenix Release Please

    Arize-ai/phoenix

    Bump the next release-please version for a Phoenix Python package (arize-phoenix, arize-phoenix-client, arize-phoenix-evals, arize-phoenix-otel) by opening a PR with a Release-As commit footer.

    12k GitHub stars~708 tokensUpdated yesterday
    AI & LLM EngineeringAuto-check passed

  • Olore Langfuse Latest

    olorehq/olore

    Local Langfuse documentation reference (latest). An agent skill from olorehq/olore.

    104 GitHub stars~1.2k tokensUpdated yesterday
    AI & LLM EngineeringAuto-check passed

  • Telemetry Analyzer

    IBM/ibm-watsonx-orchestrate-adk

    Official

    A skill your agent uses when the user wants to analyze agent telemetry traces to find bugs and get fix recommendations — walks through exporting traces from a local or remote watsonx Orchestrate…

    178 GitHub stars~10k tokensUpdated 3 days ago
    DevelopmentAuto-check: notes

  • Ak Dev New Tracing Provider

    yaalalabs/agent-kernel

    Step-by-step guide for adding a new observability/tracing provider to Agent Kernel.

    192 GitHub stars~3.5k tokensUpdated yesterday
    DevOps & CloudAuto-check passed

More from jeremylongshore/tons-of-skills-marketplace

All 3,342 skills in this repo

  • Performing Security Code Review

    jeremylongshore/tons-of-skills-marketplace

    Execute this skill enables AI assistant to conduct a security-focused code review using the security-agent plugin.

    2.8k GitHub starsUsed in 2 repos~1.3k tokens
    Auto-check: notes

  • Adapting Transfer Learning Models

    jeremylongshore/tons-of-skills-marketplace

    Build this skill automates the adaptation of pre-trained machine learning models using transfer learning techniques.

    2.8k GitHub stars~1.1k tokensUpdated today
    Auto-check passed

  • Agent Context Loader

    jeremylongshore/tons-of-skills-marketplace

    Execute proactive auto-loading: automatically detects and loads agents.md files.

    2.8k GitHub stars~1.1k tokensUpdated today
    Auto-check passed

  • Aggregating Performance Metrics

    jeremylongshore/tons-of-skills-marketplace

    Aggregate and centralize performance metrics from applications, systems, databases, caches, and services.

    2.8k GitHub stars~1.2k tokensUpdated today
    Auto-check passed

  • Analyzing Capacity Planning

    jeremylongshore/tons-of-skills-marketplace

    Execute this skill enables AI assistant to analyze capacity requirements and plan for future growth.

    2.8k GitHub stars~947 tokensUpdated today
    Auto-check passed

  • Analyzing Database Indexes

    jeremylongshore/tons-of-skills-marketplace

    Process use when you need to work with database indexing. An agent skill from jeremylongshore/tons-of-skills-marketplace.

    2.8k GitHub stars~2k tokensUpdated today
    Auto-check passed

Works with

Categories

Questions about Langfuse Install Auth

What does Langfuse Install Auth do?

Install and configure Langfuse SDK authentication for LLM observability. Langfuse Install Auth is an agent skill from jeremylongshore/tons-of-skills-marketplace. Install and configure Langfuse SDK authentication for LLM observability.

When should I use Langfuse Install Auth?

Langfuse Install Auth fits situations like: setting up a new Langfuse integration; configuring API keys; initializing Langfuse tracing in your project; with phrases like install langfuse.

How do I install Langfuse Install Auth in Claude Code?

Run `npx skills add jeremylongshore/tons-of-skills-marketplace --skill langfuse-install-auth -a claude-code`. Or copy the skill folder (skills/.curated/langfuse-install-auth in jeremylongshore/tons-of-skills-marketplace) into .claude/skills/langfuse-install-auth in your project. Claude Code loads it when a task matches its description.

How do I install Langfuse Install Auth in Codex?

Run `npx skills add jeremylongshore/tons-of-skills-marketplace --skill langfuse-install-auth -a codex`. Or copy the skill folder (skills/.curated/langfuse-install-auth in jeremylongshore/tons-of-skills-marketplace) into .agents/skills/langfuse-install-auth in your project. Codex loads it when a task matches its description.

Can I use Langfuse Install Auth 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 jeremylongshore/tons-of-skills-marketplace --skill langfuse-install-auth -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/langfuse-install-auth, .gemini/skills/langfuse-install-auth, .github/skills/langfuse-install-auth and .opencode/skills/langfuse-install-auth in your project.

What does Langfuse Install Auth need to run?

Going by SKILL.md and its folder, Langfuse Install Auth needs the command-line tools its instructions call (npm and pip) and credentials named LANGFUSE_PUBLIC_KEY and LANGFUSE_SECRET_KEY. Our summary lists: Python 3; Node.js; A credential in LANGFUSE_PUBLIC_KEY; A credential in LANGFUSE_SECRET_KEY. Its frontmatter pre-approves these tools: Read, Write, Edit, Bash(npm:*), Bash(pip:*), Bash(pnpm:*), Grep. Compatibility (from SKILL.md): Designed for Claude Code.

Does Langfuse Install Auth access the network?

SKILL.md names 2 domains. In commands or code: cloud.langfuse.com; the agent is likely to contact it when it follows the instructions. As links in the text: langfuse.com. This is read from the text; nothing was executed.

Is Langfuse Install Auth safe to install?

Our automated static check of SKILL.md found notes only (mentions a .env file), nothing it rates as a warning. It is not a guarantee. Review the folder before installing.

What licence does Langfuse Install Auth use?

Langfuse Install Auth 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 Langfuse Install Auth use?

About 1.7k tokens (SKILL.md is roughly 6.8k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Langfuse Install Auth?

Skills that share tags, products or a category with Langfuse Install Auth: Agentsop Observability Setup (agentsope/SkillAlchemy, 436 stars), Phoenix Integration Snippets (Arize-ai/phoenix, 12k stars), Phoenix Release Please (Arize-ai/phoenix, 12k stars) and Olore Langfuse Latest (olorehq/olore, 104 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Langfuse Install Auth?

jeremylongshore (a GitHub user) maintains it in jeremylongshore/tons-of-skills-marketplace, which has 2,827 GitHub stars. The repository holds 3,342 skills in this directory. The repository was last updated on October 10, 2026.

Source: jeremylongshore/tons-of-skills-marketplace on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.