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Found 172 Skills
Use when you have an approved implementation plan document and need to execute it step by step. Triggers on /execute command, when transitioning from planning with an approved plan, or when resuming execution of a partially completed plan. Provides batch-based execution with TDD, checkpoint reviews, and verification gates.
Track long-horizon objectives across multiple sessions with milestone checkpoints, progress persistence, and drift detection
Use when you need to perform I2 (Implementation Execution) in the Spec Pack of sdlc-dev, implement in batches with `{FEATURE_DIR}/implementation/plan.md` as the only SSOT, run minimal verification, write back audit information, and report at batch checkpoints; stop immediately when encountering blocking or clarification required items.
Design, validate, and plan a startup from scratch. Covers market research, competitive analysis, business model, brand identity, product definition, financial projections, and validation experiments. Trigger when the user has a startup idea to explore, wants to validate a business concept, needs a business plan or lean canvas, asks for market sizing or competitive landscape, wants brand positioning or go-to-market strategy, or says anything like "I have an idea for..." or "is this idea worth pursuing". Also handles resuming from a previous checkpoint.
Rate-limit-resilient pipeline with checkpoint/resume for long multi-phase sessions. Saves progress to .claude/pipeline-state.json after each phase. Use when starting a complex multi-phase task that risks hitting rate limits, when resuming an interrupted session, or when orchestrating work spanning commits, GitHub issues, and large file changes.
Use when breaking work into discrete steps, tracking progress through multi-step implementations, or managing implementation task lists. Triggers when an approved plan needs to be converted into tracked tasks, when progress reporting is needed during execution, or when checkpoint reviews are required between task batches.
Start, query, and stop a network-specific TAO inference microservice ({network_arch}-inference-microservice) by delegating container execution to the appropriate platform skill. Handles container image resolution, job-payload JSON construction, and the service registry. Use when the user wants to run inference on a TAO model checkpoint using a microservice container, deploy a TAO inference endpoint, or stop a running inference container.
Refactor PyTorch code to improve maintainability, readability, and adherence to best practices. Identifies and fixes DRY violations, long functions, deep nesting, SRP violations, and opportunities for modular components. Applies PyTorch 2.x patterns including torch.compile optimization, Automatic Mixed Precision (AMP), optimized DataLoader configuration, modular nn.Module design, gradient checkpointing, CUDA memory management, PyTorch Lightning integration, custom Dataset classes, model factory patterns, weight initialization, and reproducibility patterns.
Controlled plan execution with human review checkpoints - loads plan, executes in batches, pauses for feedback. Supports one-go (autonomous) or batch modes.
Scan an experiment repo and generate a complete paper outline (H1/H2/H3) with user approval checkpoints at each level, then generate body text with evidence annotations, citations, and bilingual output. Python ML repos. 扫描实验仓库，逐级生成论文大纲（H1/H2/H3），每级用户确认后推进， 然后生成带证据标注、引用和双语输出的正文文本。
Generate images via the Stable Diffusion WebUI / Forge HTTP API (AUTOMATIC1111-compatible `/sdapi/v1/*`). Use when the user wants to (1) discover or pick a model / extra module (TE/VAE) / sampler / scheduler / style preset from a running sd-webui server, (2) generate an image with a given prompt (txt2img), (3) check generation progress, (4) cancel/interrupt an in-flight generation, (5) inspect or change a global sd-webui option (e.g. active checkpoint), or (6) test connectivity. This skill talks to a *generic* sd-webui-compatible server (AUTOMATIC1111, Forge, reForge, sd-webui-forge-classic). Do NOT trigger for requests that are purely writing the prompt itself.
Generates a comprehensive milestone progress review including feature completeness, quality metrics, risk assessment, and go/no-go recommendation. Use at milestone checkpoints or when evaluating readiness for a milestone deadline.