Langfuse skill

Langfuse CLI is a command-line tool for accessing Langfuse APIs from agent workflows, scripts, and CI/CD. It exposes Langfuse data and operations including traces, scores, datasets, and experiment runs, enabling coding agents and developers to investigate production behavior and evaluation results from the terminal.

Langfuse is an open-source LLM engineering platform for developing, monitoring, evaluating, and debugging AI applications. It ingests traces for LLM calls and related operations such as retrieval, embeddings, and agent actions, with integrations including OpenTelemetry, LangChain, the OpenAI SDK, LiteLLM, and other LLM frameworks. Its features include prompt management with version control and collaborative iteration, LLM-as-a-judge and code-based evaluations, user feedback and manual labeling, datasets for test sets and benchmarks, trace replay and debugging, metrics, and a playground for testing prompts and model configurations. Langfuse exposes APIs and typed Python and JavaScript/TypeScript SDKs for custom LLMOps workflows. It is available as a managed cloud service or for self-hosting with Docker Compose, virtual machines, Kubernetes via Helm, or Terraform templates.

Langfuse Workshop is a step-by-step learning resource about applying Langfuse across the AI engineering loop. It uses a small TypeScript Dad IT Support Agent, named Specs, to teach tracing agent steps, managing prompts, monitoring production behavior, building datasets, running experiments, and evaluating changes. The workshop includes self-guided learner lessons, instructor notes, preparation materials, checkpoint branches, a runnable sample application, and helper scripts; its material is maintained in the public langfuse/langfuse-workshop repository. The sample agent uses an OpenAI tool-calling loop with two local tools, and the monitoring exercises cover user disagreement and all-caps frustration. The workshop is licensed under MIT and recommends Langfuse Cloud because self-hosted instances may not match the features used in the lessons.

ffmpeg-skill is an agent skill that gives Claude Code, Cursor, Codex, and other agents a local video- and audio-editing workflow built on FFmpeg and ffprobe. It uses a probe → edit, preferring stream copying where possible → check → verify process, with typed Python scripts rather than shell strings. Its 21 tools cover cutting, joining, silence removal, duration and aspect-ratio fitting, captions, overlays, graphics, HDR-to-SDR conversion, LUTs, audio cleanup, loudness, synchronization with drift correction, multicamera editing, delivery checks, project rendering, and batch processing. Each tool supports structured results and dry runs, and the machine-readable contract generates an MCP interface whose tool definitions are derived from the scripts. The skill runs locally without cloud services, API keys, or Python dependencies beyond the standard library; it requires FFmpeg 5.0 or later. It is a tool for local, agent-controlled workflows that probe, edit, verify, and render video.

cli-faq-shortcuts is an agent skill that analyzes a developer's coding-agent history and turns repeated requests into project-specific slash-command shortcuts for Claude Code, Codex, and Cursor. Its local extractor reads prompts from the relevant Claude Code, Codex, and Cursor history files, excluding subagent turns and scripted runs. The agent groups differently worded prompts by intent, counts recurring asks, checks existing shortcuts and project tools, and presents candidates for the user to select. Each selected shortcut is written as a SKILL.md file under the project’s .claude/skills directory, linked through .agents/skills so the supported agents can load it; the repository also records mappings in CLAUDE.md or AGENTS.md. Shortcuts can point to existing scripts and queries, include project-specific cautions, and use a dry run before actions that write or send data. The extractor can be run independently with Python and reads local files without making network calls. The repository supports installation on macOS, Linux, and Windows, and is licensed under Apache-2.0.