Loading...
Loading...
Found 172 Skills
This skill implements a specific task from a project's ROADMAP.md file. It should be used when the user wants to work on a roadmap action item by its ID (e.g., '1.1', '2.3'). Triggered by requests like '/do-task 1.1', '/do-task 2.3', or 'do task 3.1'. Works alongside the project-init skill (which creates the roadmap) and the checkpoint skill (which commits afterward).
This skill should be used when the user has a written implementation plan to execute in a separate session with review checkpoints.
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. WHEN: event hub SDK error, service bus SDK issue, messaging connection failure, AMQP error, event processor host issue, message lock lost, message lock expired, lock renewal, lock renewal batch, 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, batch processing lock, session lock expired, idle timeout, connection inactive, link detach, slow reconnect, session error, duplicate events, offset reset, receive batch.
Builds, deploys, manages, debugs, configures, and optimizes serverless applications on AWS using Lambda, API Gateway, Step Functions, EventBridge, and SAM/CDK. Covers cold starts, CORS debugging, event source mappings, troubleshooting, concurrency, SnapStart, Powertools, function URLs, EventBridge Scheduler, Lambda layers, Durable Functions, durable execution, checkpoint-and-replay, and production readiness. Use when the user mentions Lambda, API Gateway, Step Functions, SAM templates, CDK serverless stacks, DynamoDB stream triggers, SQS event sources, cold starts, timeouts, 502/504 errors, throttling, concurrency, CORS, Powertools, Durable Functions, durable execution, checkpoint-and-replay, or any event-driven architecture on AWS, even if they don't say "serverless." Do NOT use for EC2, ECS/Fargate containers, or Amplify hosting.
Code instrumentation for timing workloads. Two scenarios: (1) Training loop — inject manual timing to report per-iteration latency, throughput (samples/sec), and data load time. (2) Standalone kernel/op — write CUDA event timing code with warmup, per-iteration statistics, and anti-pattern avoidance. Also covers NVTX annotation for labeling profiler timelines. NOT for: running or analyzing profiler tools (nsys, ncu, Nsight Systems, Nsight Compute), writing kernels (Triton, CuTe, CUDA), applying optimizations (CUDA Graphs, gradient checkpointing, fusion), or interpreting roofline/SOL% metrics. Triggers: "measure throughput", "benchmark this function", "time my training loop", "samples per second", "NVTX annotate", "instrument my dataloader", "data load time", "kernel timing", "how do I time".
Anti-footgun protocol for AI-assisted coding. Always active during coding tasks to enforce simplicity-first thinking, surface assumptions, and prevent scope creep. Explicit checkpoints available via "cg pre", "cg post", "cg simplify". Triggers on: any coding task, code review requests, refactoring, or when user says "cg" or "check".
This skill should be used at natural checkpoints (after completing complex tasks, at session end, or when friction occurs) to reflect on skill and process execution and identify targeted improvements. Use when experiencing confusion, repeated failures, or discovering new patterns that should be codified into skills for smoother future operation.
LangGraph state-machine design and debugging for `StateGraph`, node/edge routing, checkpoints, `interrupt`, and HITL flows. Use when building or troubleshooting graph-based agents with conditional edges and thread state.
Use when "training LLM", "finetuning", "RLHF", "distributed training", "DeepSpeed", "Accelerate", "PyTorch Lightning", "Ray Train", "TRL", "Unsloth", "LoRA training", "flash attention", "gradient checkpointing"
Save complete conversation as checkpoint. Only when user explicitly requests ("save session", "checkpoint this"). Use nmem t save to automatically import coding sessions.
FORGE Autopilot — Intelligent autonomous mode. FORGE analyzes the project state, automatically decides the next action, and orchestrates all agents until completion. Configurable checkpoints for human review. Usage: /forge-auto or /forge-auto "specific objective"
Evidence-based memory optimization from real usage patterns. Analyzes recall performance, identifies bottlenecks, suggests consolidation/pruning/enrichment, and tracks improvement over time via checkpoint Q&A.