Use this skill when approved requirements and design need to be decomposed into tasks.md for Phase 3 of a Spec-Driven change. It creates atomic, traceable implementation and testing tasks, validates the plan, and should not be used to design architecture or write implementation code.
Manten testing library patterns - standalone imports via AsyncLocalStorage, async tests, describe groups, hooks, snapshots, timeouts, retries, and concurrency. Use when writing tests with manten, running node test files, or setting up a no-config test suite.
Guides continuous privacy compliance monitoring implementation including automated control testing, evidence collection automation, real-time compliance dashboards, alert-based remediation workflows, regulatory change integration, and deviation management. Covers GRC platform configuration, control framework mapping, and compliance-as-code approaches. Keywords: continuous compliance, automated monitoring, evidence collection, dashboard, regulatory change, compliance-as-code.
Use when multiple experiments or analyses have accumulated and their findings need to be interpreted together
Guides privacy audit sampling methodology including statistical and non-statistical sampling, sample size determination, stratification techniques, attribute sampling for compliance testing, confidence level selection, tolerable deviation rates, and extrapolation of results to the population. Keywords: audit sampling, statistical sampling, attribute testing, sample size, confidence level, stratified sampling, privacy audit.
Research standards/patterns via MCP Ref. Generates Standards Research for Story Technical Notes subsection. Reusable worker.
Research best practices via MCP Ref/Context7 and create documentation (guide/manual/ADR). Single research, multiple output types.
Classify cleanup candidates and apply conservative quarantine moves with reversible manifests.
Investigar cómo resuelven el mismo problema otras herramientas. Activar cuando el usuario quiera hacer un analisis competitivo, saber que hace la competencia, evaluar alternativas existentes o realizar benchmarking de mercado.
Usar para testing exploratorio con sesiones documentadas. También: probar sin script, buscar bugs, testing manual, edge cases, sesión de testing.
Run bioinformatics analyses using Lobster AI - single-cell RNA-seq, bulk RNA-seq, literature mining, dataset discovery, quality control, and visualization. Use when analyzing genomics data, searching for papers/datasets, or working with H5AD, CSV, GEO/SRA accessions, or biological data. Requires lobster-ai package installed.
Quantum physics simulation library for open quantum systems. Use when studying master equations, Lindblad dynamics, decoherence, quantum optics, or cavity QED. Best for physics research, open system dynamics, and educational simulations. NOT for circuit-based quantum computing—use qiskit, cirq, or pennylane for quantum algorithms and hardware execution.
Autonomous molecular dynamics simulation pipeline inspired by DynaMate (2026). Designs, executes, and analyzes complete MD workflows for protein and protein-ligand systems. Covers structure retrieval, system preparation, minimization, equilibration, production, and trajectory analysis (RMSD, RMSF, hydrogen bonds, binding free energy). Uses OpenMM as the primary engine with AmberTools for preparation. Self-correcting — detects and fixes common simulation failures. Use when users ask for MD simulations, protein stability analysis, binding free energy calculations, or "跑个分子动力学模拟". Requires OpenMM and optionally AmberTools.
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.
Google quantum computing framework. Use when targeting Google Quantum AI hardware, designing noise-aware circuits, or running quantum characterization experiments. Best for Google hardware, noise modeling, and low-level circuit design. For IBM hardware use qiskit; for quantum ML with autodiff use pennylane; for physics simulations use qutip.
De novo protein binder design using PXDesign. Use this skill when designing non-antibody protein binders against a target structure. Covers YAML config creation, CLI invocation, output parsing, and result interpretation. For antibody/nanobody binders, use proteus-ab instead. For structure prediction only, use proteus-fold. For scoring and screening, use proteus-scoring and proteus-screening.
Antibody and nanobody binder design using Proteus-AB (BoltzGen diffusion + Protenix refolding). Covers entity YAML specification, CLI invocation, protocol selection (nanobody-anything / antibody-anything), MSA modes, and output parsing. Use this skill whenever the user needs to design an antibody or nanobody binder against a protein target.
De novo protein binder design using PXDesign. Use this skill when designing non-antibody protein binders against a target structure. Covers YAML config creation, CLI invocation, output parsing, and result interpretation. For antibody/nanobody binders, use boltzgen instead. For structure prediction only, use proteus-fold. For scoring and screening, use by-scoring and by-screening.
Deep academic research for antibody design campaigns — target analysis, literature review, prior art search, epitope identification. Uses an 8-phase pipeline with quality gates and persistent memory. Use this skill whenever researching a protein target, starting a new design campaign, investigating prior art, analyzing epitopes, reviewing literature for design strategy, or when the user mentions target research, literature search, or prior art in the context of protein/antibody design.
Deep academic research for antibody design campaigns — target analysis, literature review, prior art search, epitope identification. Uses an 8-phase pipeline with quality gates and persistent memory. Use this skill whenever researching a protein target, starting a new design campaign, investigating prior art, analyzing epitopes, reviewing literature for design strategy, or when the user mentions target research, literature search, or prior art in the context of protein/antibody design.
