Prepare and publish stable Agent Lightning releases through the repository's version bump, pull-request checks, merge, tag, PyPI trusted-publishing, and versioned-documentation workflows. Use when asked to plan, cut, verify, or explain a release; treat nightly TestPyPI builds as a separate path.
Provides the action space, tradeoffs, and evaluation context for improving an editable AI agent against a benchmark while preserving its deployment contract. Use when optimizing agent accuracy, cost, latency, or reliability.
Write or review Pydantic Field(description=...) text for ZenML stack component configs. Use when adding, editing, or reviewing config fields in src/zenml/integrations//flavors/ or any StackComponentConfig subclass, or when scripts/validatedescriptions.py fails.
Use ONLY for abstract DataChain SDK questions — API usage, method signatures, or code patterns — when no specific dataset or bucket is referenced. If the request mentions creating, saving, listing, exploring datasets or buckets, use datachain-knowledge instead.
Use when asked about Studio job analytics — compute hours, user spend, failure rates, cost estimation, cluster usage. Generates and maintains dc-knowledge/jobs/index.md.
Use whenever datasets, cloud storage buckets, or data pipelines are mentioned — creating, saving, querying, listing, exploring, deleting, or processing data in S3, GCS, Azure Blob, or local storage. Also use when running any script that may create datasets as a side effect. Maintains a knowledge base at dc-knowledge/…
PyTorch library for audio generation including text-to-music (MusicGen) and text-to-sound (AudioGen). Use when you need to generate music from text descriptions, create sound effects, or perform melody-conditioned music generation.
Discover dependencies and prepare or execute Kitaru core and plugin releases, including version proposals, Kitaru UI selection, release PRs, ordered tag commands, artifact verification, and recovery. Use when a user asks what a release depends on or wants to prepare, cut, publish, verify, or recover a Kitaru, Kitaru…
Add, reuse, or change a frontend-specific Kitaru REST response under /api/v1/ui and its OpenAPI contract in zenml-frontend-monorepo. Use when a dashboard screen needs a purpose-built data shape, not for ordinary reusable resources or UI bundle releases.
Use when building, debugging, or deploying a Python service that touches FHIR resources, EHR APIs, CDS Hooks, clinical documents, or patient data — including writing model or agent output back into a patient record, connecting to Epic/Cerner/Medplum, or serving FHIR tools to an agent over MCP or LangChain.
🤖 Data Science & AI/ML skill suite derived from VoltAgent/awesome-agent-skills. Data pipelines, model training, evaluation, MLOps and analytical reporting. Provides 10 specialised commands for data-science, machine-learning, analytics workflows.
🤖 Data Science & AI/ML skill suite derived from BehiSecc/awesome-claude-skills. Data pipelines, model training, evaluation, MLOps and analytical reporting. Provides 10 specialised commands for data-science, machine-learning, analytics workflows.
🤖 Data Science & AI/ML skill suite derived from alirezarezvani/claude-skills. Data pipelines, model training, evaluation, MLOps and analytical reporting. Provides 10 specialised commands for data-science, machine-learning, analytics workflows.
🤖 Data Science & AI/ML skill suite derived from travisvn/awesome-claude-skills. Data pipelines, model training, evaluation, MLOps and analytical reporting. Provides 10 specialised commands for data-science, machine-learning, analytics workflows.
🤖 Data Science & AI/ML skill suite derived from shanraisshan/claude-code-best-practice. Data pipelines, model training, evaluation, MLOps and analytical reporting. Provides 10 specialised commands for data-science, machine-learning, analytics workflows.
🤖 Data Science & AI/ML skill suite derived from borghei/Claude-Skills. Data pipelines, model training, evaluation, MLOps and analytical reporting. Provides 10 specialised commands for data-science, machine-learning, analytics workflows.
🤖 Data Science & AI/ML skill suite derived from anthropics/claude-code. Data pipelines, model training, evaluation, MLOps and analytical reporting. Provides 10 specialised commands for data-science, machine-learning, analytics workflows.
🤖 Data Science & AI/ML skill suite derived from anthropics/skills. Data pipelines, model training, evaluation, MLOps and analytical reporting. Provides 10 specialised commands for data-science, machine-learning, analytics workflows.
🤖 Data Science & AI/ML skill suite derived from ComposioHQ/awesome-claude-skills. Data pipelines, model training, evaluation, MLOps and analytical reporting. Provides 10 specialised commands for data-science, machine-learning, analytics workflows.
Builds production AI/ML systems — model training, fine-tuning, MLOps pipelines, model serving, evaluation frameworks, RAG optimization, and agent orchestration at scale. Use when the user asks to build, train, or deploy ML models, set up MLOps pipelines, optimize RAG systems, create inference endpoints, or design…
🤖 Data Science & AI/ML skill suite derived from iannuttall/claude-agents. Data pipelines, model training, evaluation, MLOps and analytical reporting. Provides 10 specialised commands for data-science, machine-learning, analytics workflows.
🤖 Data Science & AI/ML skill suite derived from alirezarezvani/claude-code-tresor. Data pipelines, model training, evaluation, MLOps and analytical reporting. Provides 10 specialised commands for data-science, machine-learning, analytics workflows.