A workflow for working with Langfuse, a service for recording and inspecting how AI applications run. It covers documentation lookup and command-line access to traces, prompts, datasets, scores, sessions, and other records.

Use it to instrument applications, inspect or change Langfuse data, migrate prompts, debug traces, and follow Langfuse integration documentation.

It provides a documented way to inspect AI application behavior, debug runs, and manage recorded prompts and evaluation data. It also helps avoid relying on outdated Langfuse instructions.

How raphaelmansuy/edgequake configures Claude Code

About the project

EdgeQuake is a Rust framework that turns documents into knowledge graphs for GraphRAG, a retrieval-and-generation approach that uses linked facts to help language models find relevant information. It is used to build applications that search and generate answers from document collections.

raphaelmansuy/edgequake · 2,281 stars · on GitHub · edgequake.com

Reuse

Borrowing it

Nothing to install: this file belongs to raphaelmansuy/edgequake. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file

curl -O https://raw.githubusercontent.com/raphaelmansuy/edgequake/edgequake-main/.github/skills/langfuse/SKILL.md

Clone the repo

git clone --depth 1 https://github.com/raphaelmansuy/edgequake

Made for: Claude Code.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

README.md

[![agentmods](https://agentmods.dev/badge/skills/raphaelmansuy/edgequake/langfuse/github.svg)](https://agentmods.dev/skills/raphaelmansuy/edgequake/langfuse)

Your own site

<a href="https://agentmods.dev/skills/raphaelmansuy/edgequake/langfuse"><img src="https://agentmods.dev/badge/skills/raphaelmansuy/edgequake/langfuse/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

Your own site · 80×15

<a href="https://agentmods.dev/skills/raphaelmansuy/edgequake/langfuse"><img src="https://agentmods.dev/badge/skills/raphaelmansuy/edgequake/langfuse.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 100 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 1,881 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 1 finding. A grade says what 26 rules found in the file — not that it is safe. Third-party audits

NVIDIA SkillSpector warn 7 Sept 2026

SkillSpector: 7 findings, up to medium

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

medium MCP Rug Pull · line 7
npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.

Fix: Pin the version: npx @scope/[email protected]
medium MCP Rug Pull · line 8
npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.

Fix: Pin the version: npx @scope/[email protected]
medium MCP Rug Pull · line 9
npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.

Fix: Pin the version: npx @scope/[email protected]
medium MCP Rug Pull · line 10
npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.

Fix: Pin the version: npx @scope/[email protected]
medium MCP Rug Pull · line 55
npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.

Fix: Pin the version: npx @scope/[email protected]
medium MCP Rug Pull · line 58
npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.

Fix: Pin the version: npx @scope/[email protected]
medium MCP Rug Pull · line 61
npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.

Fix: Pin the version: npx @scope/[email protected]

How audits are shown

Origin original No closer match found in the catalogue.

Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

Model	Per session	Once invoked
Fable 5.1	$0.00100	$0.01881
Opus 5.5	$0.00040	$0.00752
Sonnet 5.5	$0.00020	$0.00376
Haiku 4.5	$0.00010	$0.00188

Measured 1mo ago against content hash 58a3d325b475, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

langfuse scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

- Bash(curl *langfuse.com/*)

.github/skills/langfuse/SKILL.md · 147 lines

How it starts

The opening of the file, as written. The whole thing — 147 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Langfuse

This skill helps you use Langfuse effectively across all common workflows: instrumenting applications, migrating prompts, debugging traces, and accessing data programmatically.

Core Principles

Follow these principles for ALL Langfuse work:

Documentation First: NEVER implement based on memory. Always fetch current docs before writing code (Langfuse updates frequently) See the section below on how to access documentation.
CLI for Data Access: Use langfuse-cli when querying/modifying Langfuse data. See the section below on how to use the CLI.
Best Practices by Use Case: Check the relevant reference file below for use-case-specific guidelines before implementing
Use latest Langfuse versions: Unless the user specified otherwise or there's a good reason, always use the latest version of Langfuse SDKs/APIs. Even if you're only creating a plan for another agent to execute, be explicit about the exact version to use.
If you guide the user through UI and are unsure about a label or location, inspect the user’s screenshots or ask to see the relevant screen. Do not assume UI labels have the exact same names as API, SDK, or CLI fields.

Use case specific references

instrumenting an existing function/application: references/instrumentation.md
migrating prompts from a codebase into Langfuse: references/prompt-migration.md
creating a prompt or changing any part of an existing prompt, including small edits and debugging/tuning: references/prompt-engineering.md
capturing user feedback (thumbs, ratings, implicit signals) as scores on traces: references/user-feedback.md
further tips on using the Langfuse CLI: references/cli.md
upgrading legacy trace-level or dataset-item evaluators to observation-level or experiment evaluators: references/trace-evaluator-upgrade.md. Use the evaluator migration guide as the primary reference.
preparing an application and Langfuse project for the v4 platform migration: references/v4-project-migration.md
judge calibration (LLM-as-a-Judge reliability, simple accuracy checks, advanced split-based validation, confusion matrices, and metric ingestion): references/judge-calibration.md
systematic error analysis — reading traces, building failure taxonomy, deciding what to fix: references/error-analysis.md
setting up CI/CD experiment gates with langfuse/experiment-action: references/ci-cd.md
submitting feedback about this skill: references/skill-feedback.md

Read the full file on GitHub · 147 lines

Files

What ships with it

12 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

1mo ago First seen · 147 lines · 100 tokens per session scan A 58a3d325b475

Subscribe to this mod's changes

langfuse is a skill published in the GitHub repository raphaelmansuy/edgequake (2,281 stars, last pushed yesterday), licensed Apache-2.0. It adds 100 tokens to every session and 1,881 once invoked, about $0.0004 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

Backend and APIs RAG and vectors Writing and docs graphrag knowledge-graph lightrag

graphify

Use for any question about a codebase, its architecture, file relationships, or project content — especially when graphify-out/ exists, where the question should be treated as a graphify query first. Turns any input (code, docs, papers, images, videos) into a persistent knowledge graph with god nodes, community…

Graphify-Labs/graphify · 76 tokens

potpie-repo-baseline

Use when establishing, refreshing, or deeply understanding a repository's baseline memory in Potpie: purpose, application type, features, services/modules, environments, deploy shape, dependencies, API contracts, datastores, integrations, ownership, and explicit preferences. The harness reads authored and…

potpie-ai/potpie · 75 tokens

potpie-infra-architecture

Use for project infra and architecture context: environments, adapters, runtime configuration, deployments, service dependencies, datastores, API contracts, ownership, incidents, and dependency blast radius.

potpie-ai/potpie · 43 tokens

potpie-project-preferences

Use before writing, modifying, reviewing, refactoring, or testing code so repo/project preferences surface: error handling, file structure, frameworks, logging, dependency choices, testing, security, API style, and naming. Also use after code work when a reusable project preference should be recorded.

potpie-ai/potpie · 63 tokens

browser-0754386d

A guide to the browser Fetch API, which sends network requests with a method, URL, headers, and optional body.

FuRongJun-1999/dsh-memory · 90 tokens

browser-2471a991

An HTTP request builder for assembling a GET request with a host and headers. HTTP is the standard format browsers and servers use to exchange web requests and responses.