csharp-mcp-server-generator
Generate a complete MCP server project in C# with tools, prompts, and proper configuration
Browse reusable Agent Skills, each with a clear purpose and practical guidance.
Generate a complete MCP server project in C# with tools, prompts, and proper configuration
Load when scaffolding a NEW OmicsClaw skill from a natural-language request — generates the skill directory layout (SKILL.md, parameters.yaml, references/, tests/) under the chosen domain. Skip when modifying an existing skill (edit its files directly) or when only routing a query (use `orchestrator`).
Senior software engineer for story execution and code implementation. Use when the user asks to talk to Amelia or requests the developer agent.
Install AgentVibes TTS voice system for BMAD agents. Gives each agent a unique voice, personality, and audio effects. Use when user wants to add voice/TTS to their BMAD setup, or when bmad-party-mode is active and agents are silent.
Scope Cursor Agent prompts for Echo-Memory development — memory families, entry scripts, project skills, and public-repo constraints. Use when vibe coding, writing .cursor/rules, or planning multi-file agent tasks in this repo.
Run Echo-Memory replay, in-domain loop/revisit, and open-domain eval v2 scripts. Use when checking HF checkpoints, editing eval/v2, or tracing CKPT → memory profile via env/memory_baseline_runtime.py.
Run Echo-Memory memory-baseline and context training recipes on Wan 2.1 1.3B. Use when training spatial/SSM/compression/context rows, editing train/*.sh launchers, or configuring DATASET_BASE_PATH for static or dynamic pools.
REQUIRED when the user asks what you remember, recall, or know from past conversations, previous sessions, cross-session memory, memory classes, or memory types. Also before using memory tools: find_memories, get_memories, store_memory, update_memory.
Builds AI agents, generates text and chat responses, produces images, synthesizes audio, transcribes speech, generates vector embeddings, reranks documents, and manages files and vector stores using the Laravel AI SDK (laravel/ai). Supports structured output, streaming, tools, conversation memory, middleware, queueing, broadcasting, and provider failover. Use when building, editing, updating, debugging, or testing any AI functionality, including agents, LLMs, chatbots, text generation, image generation, audio, transcription, embeddings, RAG, similarity search, vector stores, prompting, structured output, or any AI provider (OpenAI, Anthropic, Gemini, Cohere, Groq, xAI, ElevenLabs, Jina, OpenRouter).
Designs human-in-the-loop review points for DAG workflows. Determines what to present to the human, how to collect feedback, and how to route approve/reject/modify decisions back into the DAG. Use when adding approval gates, designing review UX, or handling human feedback in agent workflows. Activate on "human review", "approval gate", "human-in-the-loop", "human gate", "approval workflow", "user review step". NOT for executing human gates at runtime (use dag-runtime with Temporal signals), general UX design, or chatbot conversation design.