Langfuse Connector for Muse
Query LLM traces and observations; manage prompts and scores.
- What
- Query LLM traces and observations; manage prompts and scores.
- Cost
- Free
- Needs
- A Langfuse public + secret key pair (Langfuse Settings > API keys), stored as ONE combined value in `public_key:secret_key` format (e.g. `pk-lf-...:sk-lf-...`), kept in your Muse's secure vault (never paste secrets here). Note: declare your host at connect time (cloud.langfuse.com, us.cloud.langfuse.com, or self-hosted); scoring traces and adding dataset items are writes — confirm first. Langfuse has a free cloud tier.
- Install
- Copy the installer prompt below into your Muse — your agent does the rest.
A Muse agent skill for Langfuse LLM observability: browse traces and observations, list prompts and datasets, score traces, and add dataset items. Reading needs no confirmation; scoring a trace and adding dataset items are writes — the skill confirms first. Works against Langfuse Cloud (EU or US) or your self-hosted instance (declare the host at connect time). Honest note: ingested data can lag ~15–30 seconds behind a run — a missing trace may just need a moment. Langfuse has a free cloud tier. Draft: written from Langfuse's public API docs, not yet live-tested end-to-end — this listing's unverified status reflects that. No secrets in the repo.
Curated by Skill Harbor — free, open-source build (MIT) by @bluman1.
Version:
Install
Prerequisites: A Langfuse public + secret key pair (Langfuse Settings > API keys), stored as ONE combined value in `public_key:secret_key` format (e.g. `pk-lf-...:sk-lf-...`), kept in your Muse's secure vault (never paste secrets here). Note: declare your host at connect time (cloud.langfuse.com, us.cloud.langfuse.com, or self-hosted); scoring traces and adding dataset items are writes — confirm first. Langfuse has a free cloud tier. No GitHub account needed unless listed here. Install "Langfuse Connector for Muse" for me. A Muse agent skill for Langfuse LLM observability: query traces and observations, manage prompts, score traces, add dataset items. Repository: https://github.com/bluman1/muse-connectors/tree/main/connectors/langfuse 1. Fetch the SKILL.md file (and any helper files) from the repository path into a temporary folder and summarize what it does in one or two sentences. 2. Safety check: review the SKILL.md and scripts for anything suspicious (unexpected network calls, shell commands, credential harvesting). This repo should contain zero secrets in code, credentials only via the secure vault, allowed hosts declared in the SKILL.md. Verify that holds here; STOP on any red flag and tell me. 3. Install it as a skill: copy SKILL.md and its helper files into the agent's skills directory, in a folder named "langfuse". 4. Verify with no network calls: frontmatter valid, files in place. 5. Report what was installed, where, and what I still need to do myself (e.g. save my Langfuse key pair in the vault). GitHub is optional: if I have a GitHub account or the gh CLI, you may use it; otherwise public access is fine. Never require it unless it's in the prerequisites above. Rules: don't touch anything outside the temp folder and the install target. If anything looks off, stop and ask me.
Questions
How do I install a skill?
Every product page includes a copy-paste install prompt. Paste it into your Muse and it sets the skill up for you — no manual configuration.
Where does my money go?
Straight to the seller. Skill Harbor never processes payments: checkout happens on the seller’s own page, usually Stripe.
What does the ✓ next to a creator’s name mean?
It means we confirmed the identity of the person behind the listing. It says nothing about the code itself — always check a skill before installing it.