Use Angular-signal-backed table.atoms, direct template reads, computed selectors, controlled signals, value-or-updater callbacks, and external Angular Store atoms while accounting for injectTable initializer reruns.

Complete Angular v8-to-v9 migration reference: injectTable and injection context, explicit features and row-model slots, signal/atom state, FlexRender directives, type generics, prototype methods, sorting, sizing, selection, and logical pinning.

Create an Angular TanStack Table v9 table with injectTable inside injection context, explicit stable tableFeatures and columns, signal-backed data, and FlexRender structural directives or helpers.

Create an Angular injectAppTable/createAppColumnHelper abstraction with shared features/defaults, registered components, injectTableContext/injectTableCellContext/injectTableHeaderContext, and correct FlexRender component-versus-function handling.

Register Angular Table v9 instances with injectTanStackTableDevtools inside injection context. Load for reactive table registration, required options.key, enabled or undefined tables, cleanup, Angular isDevMode gating, or explicit production exports.

Read automatically reactive Alpine table APIs in bindings and own slices with Alpine.reactive getters plus on*Change or external TanStack Store atoms. Load for controlled state, updater callbacks, selector gating, atom precedence, or code incorrectly adding table.Subscribe.

Create an Alpine TanStack Table v9 table with createTable, explicit tableFeatures, Alpine.reactive data getters, x-for rendering, and FlexRender through x-html. Load for first-table setup, reactive options, or when nested Alpine directives rendered by x-html do not initialize.

Share Alpine tableFeatures, defaults, createAppTable, and createAppColumnHelper with createTableHook. Load when multiple Alpine tables repeat infrastructure; unlike JSX adapters, Alpine has no registered table/cell/header component or context registry.

Pro frontend engineering discipline. Enforces build-test-verify workflow for every web project. Never declare done until the site is built, tested, responsive, accessible, and visually verified in a real browser. Pairs with a deployment skill such as vercel-cli, where one is installed.

Create and audit truthful, accessible, publication-ready scientific figures with Matplotlib, Seaborn, or Plotly. Use for figure design, multi-panel layouts, uncertainty and missing-data displays, color/contrast review, image metadata validation, and journal export planning.

Cheminformatics toolkit for fine-grained molecular control. SMILES/SDF parsing, descriptors (MW, LogP, TPSA), fingerprints, substructure search, 2D/3D generation, similarity, reactions. For standard workflows with simpler interface, use datamol (wrapper around RDKit). Use rdkit for advanced control, custom sanitization, specialized algorithms.

Develop and review PyLabRobot lab-automation resources, liquid-handling plans, offline simulations, and supported-device integrations. Use for PyLabRobot protocols or API questions; keep physical execution behind an explicit operator safety gate.

Hardware-agnostic quantum ML framework with automatic differentiation. Use when training quantum circuits via gradients, building hybrid quantum-classical models, or needing device portability across IBM/Google/Rigetti/IonQ. Best for variational algorithms (VQE, QAOA), quantum neural networks, and integration with PyTorch or JAX. For hardware-specific optimizations use qiskit (IBM) or cirq (Google); for open quantum systems use qutip.

Author, review, migrate, simulate, and troubleshoot official Opentrons Python Protocol API v2 protocols for Flex and OT-2 robots. Use for robot-specific liquid handling, deck and labware setup, pipettes, modules, runtime parameters, liquid classes, and Opentrons App analysis. Use pylabrobot instead when one workflow must support multiple robot vendors.

Low-level plotting library for full customization. Use when you need fine-grained control over every plot element, creating novel plot types, or integrating with specific scientific workflows. Export to PNG/PDF/SVG for publication. For quick statistical plots use seaborn; for interactive plots use plotly; for publication-ready multi-panel figures with journal styling, use scientific-visualization.

Fast CLI/Python queries to 20+ bioinformatics databases. Use for quick lookups: gene info, BLAST/BLAT, viral sequence downloads, AlphaFold structures, enrichment analysis, OpenTargets, COSMIC, CELLxGENE, and 8cube mouse specificity/expression data. Best for interactive exploration and simple queries. For batch processing or advanced BLAST use biopython; for multi-database Python workflows use bioservices.

Read, inspect, and write Flow Cytometry Standard (FCS) 2.0, 3.0, and 3.1 files with FlowIO. Use for low-level FCS metadata and channel inspection, NumPy event extraction, multi-dataset files, table export, and FCS 3.1 creation; use FlowKit for compensation, cytometry transforms, gating, or FlowJo workspaces.

Design experiments and studies BEFORE data is collected — choosing a design, randomizing, blocking, and laying out treatment combinations so results are interpretable. Use whenever someone is planning a study, asks how to assign subjects/samples to groups, mentions randomization, blocking, stratification, controls, factorial or fractional-factorial designs, design of experiments (DOE), screening many factors, response-surface optimization, crossover or repeated-measures or split-plot designs, cluster/group randomization, Latin squares, plate layouts, batch/run-order effects, replication vs. pseudoreplication, or sequential/adaptive/group-sequential designs. Trigger even for informal phrasings like "how should I set up this experiment", "how do I avoid confounding", "what's the best way to test these 6 factors", or "assign these mice to conditions". For computing the sample size or power once the design is chosen, use statistical-power; for analyzing data already collected, use statistical-analysis.

Analyze, manipulate, compare, annotate, and visualize phylogenetic or other hierarchical trees with ETE 4. Use for Newick/Nexus tree I/O, topology edits and pattern matching, Robinson-Foulds comparisons, gene-tree evolutionary events and reconciliation, NCBI/GTDB taxonomy, SmartView exploration, and publication rendering. Do not use it to infer trees from raw sequences; align sequences and infer a tree first.

DiffDock and DiffDock-L molecular docking. Use for protein-small-molecule pose prediction from PDB or sequence plus SMILES/SDF/MOL2, batch docking, virtual screening, and pose-confidence interpretation. Not for binding affinity prediction.