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Specialized ML model development, training, and deployment workflow

Execute evidence-based decision-making through 6-stage causal flow. Use for known processes, operational execution, and decisions with clear cause-effect chains.

Prompt engineering standards and context engineering principles for AI agents based on Anthropic best practices. Covers clarity, structure, progressive discovery, and optimization for signal-to-noise ratio.

Generate comprehensive quality report with metrics and verification. Produces final CHAPTER_XX_VERIFICATION.md and quality_metrics.json for deployment approval.

IBM quantum computing framework. Use when targeting IBM Quantum hardware, working with Qiskit Runtime for production workloads, or needing IBM optimization tools. Best for IBM hardware execution, quantum error mitigation, and enterprise quantum computing. For Google hardware use cirq; for gradient-based quantum ML use pennylane; for open quantum system simulations use qutip.

Python-based threat modeling using pytm library for programmatic STRIDE analysis, data flow diagram generation, and automated security threat identification. Use when: (1) Creating threat models programmatically using Python code, (2) Generating data flow diagrams (DFDs) with automatic STRIDE threat identification, (3) Integrating threat modeling into CI/CD pipelines and shift-left security practi

Comprehensive GitHub release orchestration with AI swarm coordination for automated versioning, testing, deployment, and rollback management. Coordinates release-manager, cicd-engineer, tester, and docs-writer agents through hierarchical topology to handle semantic versioning, changelog generation, release notes, deployment validation, and post-release monitoring. Supports multiple release strateg

Python scripting with uv and PEP 723 inline dependencies. Use when creating

Fast Python environment management with uv (10-100x faster than pip). Triggers on: uv, venv, pip, pyproject, python environment, install package, dependencies.

Observability patterns for Python applications. Triggers on: logging, metrics, tracing, opentelemetry, prometheus, observability, monitoring, structlog, correlation id.

You are a Python project architecture expert specializing in scaffolding production-ready Python applications. Generate complete project structures with modern tooling (uv, FastAPI, Django), type hint

Automate Render tasks via Rube MCP (Composio): services, deployments, projects. Always search tools first for current schemas.