nwb-validation
Validates NWB files using NWB Inspector and provides intelligent correction recommendations
Validates NWB files using NWB Inspector and provides intelligent correction recommendations
Probe and test SDR hardware capabilities (RTL-SDR, SDRplay, HackRF, etc.). Use when verifying device detection, discovering supported sample rates and gains, testing antenna ports, or troubleshooting SDR hardware issues.
Complete technical reference for the professional mixer system architecture, audio routing, recording implementation, and all internal mechanics
Adjust SDR radio settings (frequency, gain, squelch, bandwidth, filters, AGC) in WaveCap-SDR. Use when changing tuning parameters, optimizing reception, or configuring channels.
Create and manage WaveCap-SDR recipe templates for common capture scenarios. Use when setting up new band plans, creating presets for trunking systems, or building reusable multi-channel configurations for marine/aviation/broadcast monitoring.
Python for engineering analysis, numerical computing, and scientific workflows using NumPy, SciPy, SymPy
Computational methods for statistical inference and optimization
Perform observational constraint (Emergent Constraint, EC) analysis for climate research. Use historical observations to constrain future climate projections from CMIP6 multi-model ensembles, reducing prediction uncertainty. Includes inter-model regression analysis, EC relationship establishment, physical mechanism diagnostics (residual analysis, teleconnection pathways, Walker circulation, lead-lag correlation, SVD), uncertainty quantification (variance reduction, confidence intervals), and reliability assessment (binning analysis, random EC comparison). Use when conducting observational constraint analysis, CMIP multi-model evaluation, reducing prediction uncertainty, validating inter-model relationships, or climate teleconnection research. Applicable to any climate variable pairs (e.g., SST-TAS, precipitation-circulation).
Structured methodology for constructing and verifying mathematical proofs in statistical research
Digital forensics and malware analysis for evidence collection and investigation
Design and document statistical algorithms with pseudocode and complexity analysis
Deep analysis workflows for World Weaver memory systems, code, and architecture
Design and implementation of comprehensive simulation studies
Numerical algorithms and computational techniques for statistics
Cryptographic algorithms, protocols, and implementations for secure data protection
Monte Carlo, SDE simulation, Brownian/jump processes, discretization schemes.
NumPy for matrix operations, FFT, linear algebra, and numerical computations in marine engineering
Framework for computational fluid dynamics simulations using Python. Use when running fluid dynamics simulations including Navier-Stokes equations (2D/3D), shallow water equations, stratified flows, or when analyzing turbulence, vortex dynamics, or geophysical flows. Provides pseudospectral methods with FFT, HPC support, and comprehensive output analysis.
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.
Six-phase protocol for adapting methods across research domains
Execute deep research protocols using the Falcon specialized research framework.