Skill UI

Guides ML engineers through dataset prep, PEFT strategy selection, LoRA/QLoRA adapter setup, training monitoring, and deployment checks for practical LLM fine-tuning, quantization, and adapter merge workflows.

Fine-tune LLMs with TRL’s RLHF toolkit, covering SFT, DPO, PPO/GRPO and reward model training so you can align HuggingFace Transformers with human preferences or feedback in post-training workflows.

This workflow connects to the Fireflies.ai API via GraphQL to fetch and process detailed meeting transcripts. It handles speaker-diarized data, extracting structured insights such as action items, key topics, sentiment analysis, and speaker breakdowns. It enables the creation of comprehensive meeting intelligence reports and robust downstream pipelines. Use this when you need to automate the retrieval, summarization, or deep analysis of recorded meeting content.

Automates FlowiseAI workflows by orchestrating Rube MCP and Composio tools; always searches current tool schemas, validates active Flowiseai connections, and executes schema-compliant multi-tool calls with session reuse.

Automate Composio Gamma workflows by querying Rube MCP for current tool schemas, managing Gamma connections, and executing schema-compliant tool calls with session-aware workflows.

Gastown is a robust multi-agent orchestration system designed for Claude Code. It enables the simultaneous execution of multiple AI agents on complex projects. It manages the entire development lifecycle, from setting up workspaces and tracking work items (beads) to managing agent lifecycles (polecats/crew) and merging final code (Refinery). Use it when coordinating complex, parallel AI tasks.

Automates Gemini operations by walking through Rube MCP/Composio tool discovery, connection management, and execution steps, ensuring schema-aware usage, memory handling, and session reuse for reliable flows.

A comprehensive guide to building enterprise-grade AI applications using Firebase Genkit. This skill covers the full development lifecycle, including implementing advanced RAG systems, multi-step tool-calling agents, and complex workflows across Node.js, Python, and Go. It teaches best practices for schema validation (Zod/Pydantic), robust error handling, OpenTelemetry tracing, and deploying reliably to Firebase Functions or Cloud Run.

Master Google Cloud’s Agent Development Kit and Starter Pack to build containerized multi-agent systems, automate RAG workflows, and deploy production-ready agents via Cloud Run, GKE, Agent Engine, or CI/CD pipelines.

Automates Google Cloud Vision workflows by discovering tools, managing the Composio Rube MCP connection, and executing schema-compliant operations via RUBE_MULTI_EXECUTE_TOOL.

Automate Google Photos workflows through Rube MCP (Composio) to list and manage albums, upload or batch-create media, search items, and organize albums using the provided toolkit tools and schema-aware commands.

Gradient Clipping Helper automates ML training work by guiding gradient clipping workflows, generating production-ready code and configs, and validating outputs for PyTorch, TensorFlow, and related pipelines.