MCP servers and skills: search, filter by where they run, and compare.
Run evaluations for Hugging Face Hub models using inspect-ai and lighteval on local hardware. Use for backend selection, local GPU evals, and choosing between vLLM / Transformers / accelerate. Not for
OfficialSkillApache-2.0★ 11k in collectionNo key
Creates, optimizes, and iteratively refines agent prompts, system prompts, developer prompts, and reusable prompt templates. Use when asked to improve a prompt, optimize a system prompt, rewrite an ag
in the skill textmore reliable, port prompts between OpenAI, Claude, or Gemini, or build prompt evals. # Prompt Optimizer Optimize prompts with evals. Keep every instruction, example, and external context
OfficialSkillApache-2.0★ 1.1k in collectionNo key
Develop AI-powered applications using Genkit in Python. Use when the user asks about Genkit, AI agents, flows, or tools in Python, or when encountering Genkit errors, import issues, or API problems.
in the skill textimport Middleware, ToolApproval, ...` - FastAPI: `from genkit_fastapi import serve_agent, serve_flow` - Evals: `from genkit_evaluators import register_genkit_evaluators` ## Workflow 1. **Agent or flow
OfficialSkillApache-2.0★ 21k in collectionNo key
Use to summarize a recorded video via the LVS summarization microservice (HITL-gated) with a VLM fallback. Not for report generation or live RTSP captioning.
in the skill textlives in `references/`. ## Examples Worked end-to-end examples are kept under `evals/` (each `*.json` manifest contains a runnable scenario) and inline in the per-workflow
OfficialSkillApache-2.0★ 3.6k in collectionNo key
Who stands behind it
Who stands behind it
