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Found 104 Skills
Controls InnerClaude instances on Sprites.dev VMs for testing workflows, install patterns, and Claude-to-Claude interaction. INVOKE BEFORE any 'sprite exec', 'inner Claude', 'test this workflow', 'Claude controlling Claude', or remote VM operations. Documents the critical tmux+pipe-pane pattern that makes OuterClaude/InnerClaude interaction work. Also covers checkpoint/restore and bootstrap. (user)
Automatically creates semantic Git checkpoint commits during AI coding sessions. Replaces opaque platform checkpoints with transparent, queryable Git commits using Conventional Commits format with Git Trailers. You MUST follow this skill whenever you make code changes — commit after each meaningful edit.
Execute an approved implementation plan in a separate session with checkpoint reviews. Use after writing-plans when the user wants batched progress updates before more work continues.
Troubleshoot and resolve issues with Azure Messaging SDKs for Event Hubs and Service Bus. Covers connection failures, authentication errors, message processing issues, and SDK configuration problems. USE FOR: event hub SDK error, service bus SDK issue, messaging connection failure, AMQP error, event processor host issue, message lock lost, send timeout, receiver disconnected, SDK troubleshooting, azure messaging SDK, event hub consumer, service bus queue issue, topic subscription error, enable logging event hub, service bus logging, eventhub python, servicebus java, eventhub javascript, servicebus dotnet, event hub checkpoint, event hub not receiving messages, service bus dead letter DO NOT USE FOR: creating Event Hub or Service Bus resources (use azure-prepare), monitoring metrics (use azure-observability), cost analysis (use azure-cost-optimization)
Expert in LangGraph - the production-grade framework for building stateful, multi-actor AI applications. Covers graph construction, state management, cycles and branches, persistence with checkpointers, human-in-the-loop patterns, and the ReAct agent pattern. Used in production at LinkedIn, Uber, and 400+ companies. This is LangChain's recommended approach for building agents. Use when: langgraph, langchain agent, stateful agent, agent graph, react agent.
Pragmatic qualitative analysis for interview data in sociology research. Guides you through systematic coding, interpretation, and synthesis with quality checkpoints. Supports theory-informed (Track A) or data-first (Track B) approaches.
Use this skill when implementing tasks according to Conductor's TDD workflow, handling phase checkpoints, managing git commits for tasks, or understanding the verification protocol.
Coordinate a cross-functional star-team workflow (Product Manager, Principal Engineer, Backend, Frontend, QA/Security, DevOps) with mandatory architecture and code-review checkpoints. Use when a request needs end-to-end product delivery, multi-role collaboration, or explicit role-based outputs (PM/PE/Backend/Frontend/QA/DevOps), or when the user asks for "star team", "cross-functional", "full lifecycle", or "multi-role" planning.
Adds PyTorch FSDP2 (fully_shard) to training scripts with correct init, sharding, mixed precision/offload config, and distributed checkpointing. Use when models exceed single-GPU memory or when you need DTensor-based sharding with DeviceMesh.
Save complete conversation as checkpoint. Only when user explicitly requests ("save session", "checkpoint this"). Use nmem t save to automatically import coding sessions.
Execute an approved implementation plan exactly and safely. Use when a plan already exists (for example in docs/plans/...) and work must be carried out phase-by-phase with verification checkpoints, status tracking, and final execution reporting.
Provides PyTorch-native distributed LLM pretraining using torchtitan with 4D parallelism (FSDP2, TP, PP, CP). Use when pretraining Llama 3.1, DeepSeek V3, or custom models at scale from 8 to 512+ GPUs with Float8, torch.compile, and distributed checkpointing.