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From langfuse
Queries Langfuse API resources (traces, prompts, datasets, scores, sessions) via CLI and fetches current documentation for instrumentation, prompt migration, and error analysis.
npx claudepluginhub joshuarweaver/cascade-ai-ml-engineering --plugin langfuse-skillsHow this skill is triggered — by the user, by Claude, or both
Slash command
/langfuse:langfuseThis skill is limited to the following tools:
The summary Claude sees in its skill listing — used to decide when to auto-load this skill
This skill helps you use Langfuse effectively across all common workflows: instrumenting applications, migrating prompts, debugging traces, and accessing data programmatically.
Provides Langfuse expertise for LLM observability: tracing, prompt management, evaluations, datasets. Integrates with LangChain, LlamaIndex, OpenAI for production monitoring and debugging.
Provides expert guidance on using Langfuse for LLM observability including tracing, prompt management, evaluation, and cost monitoring. Integrates with LangChain, LlamaIndex, and OpenAI.
Debug AI agents and LLM applications via Langfuse MCP. Provides playbooks for trace inspection, exception triage, latency analysis, sessions, prompts, and datasets.
Share bugs, ideas, or general feedback.
This skill helps you use Langfuse effectively across all common workflows: instrumenting applications, migrating prompts, debugging traces, and accessing data programmatically.
Follow these principles for ALL Langfuse work:
langfuse-cli when querying/modifying Langfuse data. See the section below on how to use the CLI.langfuse/experiment-action: references/ci-cd.mdUse the langfuse-cli to interact with the full Langfuse REST API from the command line. Run via npx (no install required):
Start by discovering the schema and available arguments:
# Discover all available resources
npx langfuse-cli api __schema
# List actions for a resource
npx langfuse-cli api <resource> --help
# Show args/options for a specific action
npx langfuse-cli api <resource> <action> --help
Set environment variables before making calls:
export LANGFUSE_PUBLIC_KEY=pk-lf-...
export LANGFUSE_SECRET_KEY=sk-lf-...
export LANGFUSE_BASE_URL=https://cloud.langfuse.com # example for EU cloud. For US cloud it's us.cloud.langfuse.com, and can also be a self-hosted URL. The server must always be specified in order to access Langfuse.
If LANGFUSE_BASE_URL is used instead of LANGFUSE_HOST, run export LANGFUSE_HOST="$LANGFUSE_BASE_URL".
If not set, ask the user to set them in their shell or a .env file (do not ask them to paste keys into chat for security reasons). Keys are found in Langfuse UI → Settings → API Keys.
For common workflows, tips, and full usage patterns, see references/cli.md.
Three methods to access Langfuse docs, in order of preference. Always prefer your application's native web fetch and search tools (e.g., WebFetch, WebSearch, mcp_fetch, etc.) over curl when available. The URLs and patterns below work with any fetching method — the curl examples are just illustrative.
Fetch the full index of all documentation pages:
curl -s https://langfuse.com/llms.txt
Returns a structured list of every doc page with titles and URLs. Use this to discover the right page for a topic, then fetch that page directly.
Alternatively, you can start on https://langfuse.com/docs and explore the site to find the page you need.
Any page listed in llms.txt can be fetched as markdown by appending .md to its path or by using Accept: text/markdown in the request headers. Use this when you know which page contains the information needed. Returns clean markdown with code examples and configuration details.
curl -s "https://langfuse.com/docs/observability/overview.md"
curl -s "https://langfuse.com/docs/observability/overview" -H "Accept: text/markdown"
When you need to find information across all docs and github issues/discussions without knowing the specific page:
curl -s "https://langfuse.com/api/search-docs?query=<url-encoded-query>"
Example:
curl -s "https://langfuse.com/api/search-docs?query=How+do+I+trace+LangGraph+agents"
Returns a JSON response with:
query: the original queryanswer: a JSON string containing an array of matching documents, each with:
url: link to the doc pagetitle: page titlesource.content: array of relevant text excerpts from the pageSearch is a great fallback if you cannot find the relevant pages or need more context. Especially useful when debugging issues as all GitHub Issues and Discussions are also indexed. Responses can be large — extract only the relevant portions.
When the user expresses that something about this skill is not working as expected, gives incorrect guidance, is missing information, or could be improved — offer to submit feedback to the Langfuse skill maintainers. This includes when:
Do NOT trigger this for issues with Langfuse itself (the product) — only for issues with this skill's instructions and behavior.
When triggered, follow the process in references/skill-feedback.md.