AI Agent Skills

Choose a model architecture for a medical-imaging research question before scaffolding. Maps the task (classification, segmentation, detection, transfer), modality and d…

Zero-config Claude Code setup with enforced task scaffolding, structured memory, persistent context after compaction, plug-in code standards, optional TDD mode, and zero…

Bootstrap a reproducible LLM Observability experiment through the Python ddtrace SDK or the Node dd-trace SDK. Use for experiment, dataset, evaluator, benchmark, regress…

Claude Code infrastructure + agent team setup — rules, hooks, memory, routing, and agent installation from a guided interview. Combines infrastructure + agent team into…

Decide where files live in an ML experimentation project: reusable code in `src/<pkg>/`, one `# %%` script per experiment in `experiments/`, design notes + index in `jou…

Set up hierarchical Intent Layer (AGENTS.md files) for codebases. Use when initializing a new project, adding context infrastructure to an existing repo, user asks to se…

Orchestrate iOS/macOS app scaffolding and optional skill adoption for existing projects. Use when users want a guided wizard that can scaffold with XcodeGen and optional…

Install strict Xcode Makefile tooling for iOS/macOS projects, including build/run/test scripts with AGENT_NAME-based per-agent isolation under build/. Use when a project…

Use when designing, scaffolding, extending, or auditing a component library whose primary consumer is an AI agent — i.e. the design system needs machine-readable metadat…