Langfuse integration page creator

Langfuse integration page creator

This skill scaffolds a new integration page for the langfuse-docs site. Integration pages live as Jupyter notebooks in cookbook/integration_<slug>.ipynb and are converted to MDX by scripts/update_cookbook_docs.sh using the mapping in cookbook/_routes.json. Getting the notebook metadata block, the STEPS_START/STEPS_END wrapper, and the routes entry right is the whole job — once those are correct, the build does the rest.

What to produce

Three things, always, in the user's langfuse-docs checkout:

1. A new notebook at cookbook/integration_<slug>.ipynb that matches the house template (see "Notebook structure" below).
2. A new entry appended to cookbook/_routes.json pointing at the notebook and the target docsPath.
3. A best-effort logo download into public/images/integrations/<slug>_icon.<ext>. If fetching fails, leave a TODO for the user.

Do not run scripts/update_cookbook_docs.sh yourself — that regenerates many files and is slow (~10 min build). The user runs it when they're ready.

Step 1 — Gather what you need, up front

Before writing anything, collect the following. Ask the user for what's missing using a single AskUserQuestion batch where possible. Some answers are mutually exclusive (pick-one); some can be inferred from context.

Always ask (these determine the template and the routes entry):

• Integration name — the human-readable name (e.g., "Pydantic AI", "Fireworks AI", "Temporal"). Used in the title and intro.
• Slug — kebab-case, used in the filename, logo path, and docsPath. Default to the name lowercased with spaces → hyphens, but confirm. Example: "Pydantic AI" → pydantic-ai; "Fireworks AI" → fireworks-ai.
• Category — one of: model-providers, frameworks, gateways, other. This is the <category> segment in docsPath: "integrations/<category>/<slug>". Guidance:
  • model-providers: inference APIs (OpenAI-compatible or otherwise) — Anthropic, Cohere, Fireworks, Groq, Bedrock, Vertex, Gemini, etc.
  • frameworks: agent/app frameworks — LangChain, CrewAI, Pydantic AI, Google ADK, Temporal, Semantic Kernel, etc.
  • gateways: LLM proxies/routers — Portkey, LiteLLM proxy, TrueFoundry, OpenRouter, Kong AI, etc.
  • other: anything else — scraping (Firecrawl, Exa), UIs (Gradio, LibreChat), dev tools, etc.
• Language — python (default) or js. JS integrations use the filename prefix js_integration_<slug>.ipynb and commonly get a -js suffix in the slug when both exist (e.g., anthropic-js, claude-agent-sdk-js).
• Instrumentation pattern — pick one (this determines the template body). See references/patterns.md for full details and match it to the integration:
  • openinference — OpenInference instrumentor library (e.g., openinference-instrumentation-google-adk). Most common for agent frameworks.
  • openai-drop-in — The partner is OpenAI-compatible; use from langfuse.openai import openai. Common for inference providers (Fireworks, Groq, DeepSeek, etc.).
  • framework-native — Framework has built-in instrumentation hook (e.g., Agent.instrument_all() for Pydantic AI).
  • otel-direct — Partner emits OTel natively; configure an OTLP exporter pointing at Langfuse. Less common; used for things like Temporal, some MLflow setups.

Ask if not obvious:

• Intro blurb about the partner — one sentence ("What is X?"). If the user didn't give one and there's a URL, you can draft it and confirm.
• Logo source — if the user provided a URL, great; if not, see Step 4 for the fetch heuristic.
• Install command, env vars beyond the Langfuse ones, and a minimal runnable example — needed for the code cells. If missing, draft from docs and mark as TODO: confirm.