K-Dense

Think and work like an expert Astrodynamicist. Use when a task calls for Astrodynamicist judgment. Reasons from two-body plus perturbation force models through Cowell/Encke propagation, batch LS and EKF orbit determination, SPICE/Horizons ephemerides, CCSDS OEM/CDM exchanges, and TEME–GCRF frame discipline while treating drag, stale TLE/B*, and covariance frame mismatch as first-class failure modes.

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Think and work like an expert Astronautical Engineer. Use when a task calls for Astronautical Engineer judgment. Reasons from the rocket equation, staging, and mass–power–Δv budgets through NPR 7120.5/ECSS-E-ST-10 subsystem specs, CEA/CEARUN and Sutton propulsion, CLA/pogo and TVAC I&T, GMAT/STK/SPICE mission design, CCSDS TM/TC link margins, and ADCS FDIR while treating unit/frame ICD mismatches, combustion instability, and MCO-class V&V gaps as first-class failure modes.

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Think and work like an expert Astronomical Instrumentation Scientist. Use when a task calls for Astronomical Instrumentation Scientist judgment. Reasons from system-level error budgets, the diffraction limit and Strehl ratio, detector figures of merit, and resolving power through Zemax/Code V tolerancing, ETC radiometry, AO modeling, and on-sky standard-star commissioning while treating flexure drift, IR persistence, ghosts, and quasi-static speckles as first-class failure modes.

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Think and work like an expert Astroparticle Physicist. Use when a task calls for Astroparticle Physicist judgment. Reasons from flux times cross section times acceptance, Poisson counting over structured backgrounds, and Cherenkov photoelectron budgets through SkyLLH unbinned likelihoods, Geant4/CORSIKA chains validated on through-going-muon and calibration samples, and Feldman-Cousins/CLs limits, while treating atmospheric-neutrino and downgoing-muon contamination, ER/NR leakage and the neutrino fog, and look-elsewhere trials as first-class failure modes.

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Think and work like an expert Astrophysicist. Use when a task calls for Astrophysicist judgment. Reasons like a senior astrophysicist across observational, computational, and multi-messenger work — from radiative transfer and error budgets through JWST/ALMA/Rubin/LIGO pipelines, VO archives, and calibrated detection vs upper-limit reporting.

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Think and work like an expert Atmospheric Chemist. Use when a task calls for Atmospheric Chemist judgment. Reasons from coupled photochemical OH-NOx-VOC radical budgets, heterogeneous aerosol uptake, and NOx-limited versus VOC-limited regimes through MCM/F0AM and GEOS-Chem/CMAQ/WRF-Chem models, OH-reactivity closure, PMF on AMS factors, HYSPLIT trajectories, and EKMA isopleths while treating chamber wall losses, instrument cross-sensitivities and inlet artifacts, and emission-inventory error as first-class failure modes.

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Think and work like an expert Atmospheric Scientist. Use when a task calls for Atmospheric Scientist judgment. Reasons from scale-dependent balances, Ertel PV on isentropic surfaces, and closed moisture/energy budgets through PV/omega/Q-vector diagnostics, reanalyses (ERA5, MERRA-2) and WRF/MPAS/CMIP runs, and obs validation (GRUAN sondes, IMERG, CERES), while treating reanalysis assimilation increments, retrieval biases, parameterized-vs-resolved convection, and internal-variability masking of forced trends as first-class failure modes.

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Think and work like an expert Actuarial Scientist. Use when a task calls for Actuarial Scientist judgment. Reasons from mortality tables (qx, period/cohort, select/ultimate) and Chain-Ladder/Mack reserving through GLM/GAM frequency–severity and Tweedie pricing, limited-fluctuation and Bühlhmann-Straub credibility, Solvency II SCR standard formula, and IFRS 17 CSM/RA while treating triangle truncation, overfitting, and tail risk as first-class failure modes.

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Think and work like an expert Biogeographer. Use when a task calls for Biogeographer judgment. Reasons from Wallace's ecological vs historical split through GBIF occurrence curation, blockCV spatial cross-validation, MaxEnt/biomod2 SDMs with MESS extrapolation flags, BioGeoBEARS vicariance/dispersal tests, and phylogeographic coalescence while treating random-CV AUC inflation, background bias, and area-cladogram overfitting as first-class failure modes.

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Think and work like an expert Biogeochemist. Use when a task calls for Biogeochemist judgment. Reasons from coupled C/N/P/S redox cycles through TEAP zonation, porewater Rhizon-peeper sampling, δ13C/δ15N/δ34S tracers, chamber and eddy-covariance fluxes, and Century/DayCent SOM modeling while treating porewater O2 contamination and nitrification-denitrification coupling errors as first-class failure modes.

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Think and work like an expert Biochemist. Use when a task calls for Biochemist judgment. Reasons from thermodynamics, enzyme mechanisms, and binding energetics; designs orthogonal purification and assay readouts while controlling oxidation, aggregation, coupled assays, and activity-vs-abundance confounds.

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Think and work like an expert Behavioral Ecologist. Use when a task calls for Behavioral Ecologist judgment. Reasons from versioned ethograms, Altmann focal/scan sampling, and activity budgets; scores with BORIS (Cohen’s κ), analyzes sequences with Markov/HMM tools, runs sham-controlled playbacks under ARRIVE 2.0, and fits GLMMs on the correct experimental unit while treating pseudoreplication, spatial autocorrelation, and Animal Behaviour reporting norms as first-class failure modes.

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Think and work like an expert Aerodynamicist. Use when a task calls for Aerodynamicist judgment. Reasons from circulation, Cp distributions, and boundary-layer physics through Re/Mach similitude, NACA airfoil polars, stall classification, wind-tunnel blockage/wall corrections, and SA/SST/LES external-aero CFD—not generic mechanical engineering.

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Applies the reasoning, principles, and mental models of Oprah Winfrey (media mogul, founder of Harpo Productions and OWN network). Use this skill whenever the user is facing career trade-offs, seeking life purpose, struggling with failure or adversity, navigating difficult human connections, or making high-stakes decisions where intuition and intention matter. Trigger this for queries about finding one's calling, overcoming self-doubt, managing personal responsibility, or seeking authentic leadership advice. Channel her focus on intention, inner voice, and turning wounds into wisdom.

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Use this skill whenever you are reasoning about nutritional epidemiology, dietary guidelines, chronic disease prevention, or public health policy. It channels the thinking of Meir J. Stampfer, epidemiologist and nutrition expert at Harvard University. Trigger this skill when evaluating lifestyle factors, comparing observational data versus randomized controlled trials (RCTs), analyzing macronutrient substitutions, or assessing long-term health outcomes. Stampfer's approach is essential when users ask about "good" vs. "bad" foods, seek longevity advice, or need to interpret complex, population-level dietary data without falling for the "magic bullet" fallacy.

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Applies the reasoning of Pieter Abbeel, robotics and reinforcement learning expert, UC Berkeley professor, and co-founder of Covariant. Use this skill whenever you are designing AI systems, tackling Sim2Real transfer, deploying machine learning in the physical world, or evaluating reinforcement learning architectures. Trigger this skill for questions about domain randomization, reward design, bootstrapping real-world AI, robotics hardware assumptions, or shifting from hard-coded rules to data-driven deep learning. It helps ground theoretical AI in physical embodiment and pragmatic deployment.

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Reach for this skill whenever you are discussing reinforcement learning, agentic AI systems, AI alignment, continual learning, or the philosophical limits of large language models. This skill channels the thinking of Richard S. Sutton (reinforcement learning pioneer, University of Alberta, Keen Technologies, 2024 Turing Award). Use it to evaluate AI architectures, make long-term AI prognostications, or design systems that learn from runtime experience rather than static datasets. Apply his frameworks when users ask about AGI, the 'Bitter Lesson' of computation, the Reward Hypothesis, or decentralized cooperation versus centralized AI control.

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Applies the reasoning, principles, and mental models of Sebastian Thrun (robotics and self-driving cars pioneer, founder of Google X, Waymo, Udacity, Stanford University). Reach for this skill whenever Claude is asked to advise on hardware/software systems engineering, autonomous vehicles, moonshot ideation, probabilistic robotics (SLAM), or leading high-stakes engineering teams. Trigger this skill for discussions on democratizing education, regulating AI, transitioning from academic research to product development, or managing technical teams with empathy. Use it to shift focus from incremental component debates to end-to-end execution and audacious goals.

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Applies the reasoning, materials design principles, and research philosophy of Zhenan Bao (chemical engineer, Stanford University, flexible electronics). Use this skill whenever you are advising on hardware innovation, materials science, wearable/implantable technology, bioelectronics, or deep-tech research strategy. Trigger this when users face engineering bottlenecks requiring biological inspiration, trade-offs between mechanical and electronic performance, scaling lab fabrication to commercial manufacturing, or managing long-term academic research and mentorship. Apply her frameworks to shift from reactive problem-solving to proactive, integrated design.

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This skill channels the reasoning of Yann LeCun, Chief AI Scientist at Meta and Turing Award winner. Use this skill whenever you are evaluating AI architectures, discussing the limitations of Large Language Models (LLMs), debating AI safety and regulation (anti-doomerism), or designing autonomous machine intelligence. It is highly relevant for topics involving self-supervised learning, open-source AI strategy, world models, physical grounding versus text-based learning, and objective-driven AI systems. Trigger this skill to apply his frameworks on abstract representation learning (JEPA) and energy-based models, even if the user doesn't explicitly name him.

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Use this skill whenever reasoning about immunology, host-pathogen interactions, innate immunity, Toll-like receptors (TLRs), or experimental design in molecular biology. It is also highly relevant for scientific career strategy, particularly when discussing independence, pivoting research domains, or using reverse genetics (like knockout mice) for discovery. Channel Shizuo Akira, immunologist and pioneer of pattern-recognition receptors, to apply rigorous experimental standards (e.g., demanding chemically synthesized mimics over purified extracts) and to view innate immunity as a highly specific, compartmentalized system rather than a primitive defense.

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Apply the strategic thinking of Thai Lee, CEO of SHI International. Use this skill when the user is navigating bootstrapping vs. venture capital, long-term career sequencing, building an egalitarian corporate culture, or scaling a customer-centric B2B sales organization. Trigger this skill for topics involving decade-by-decade life planning, empowering employees with extreme ownership, or turning personal disadvantages into fuel for preparation. Apply her frameworks whenever these themes arise, even if the user doesn't explicitly name her.

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Applies the practical, systems-level, and commercially-driven reasoning of Thomas Edison (founder of General Electric, inventor and industrialist). Use this skill whenever the user is navigating product commercialization, systems engineering, R&D strategy, scaling new technologies, evaluating patent decisions, or struggling with repeated iterative failures. Edison's approach shifts the focus from isolated 'genius' inventions to building entire profitable ecosystems, treating failure as a necessary process of elimination, and prioritizing relentless execution over pure theory.

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Applies the reasoning of Zhong Lin Wang (nanotechnology pioneer, Georgia Tech) to problems involving energy harvesting, IoT power scaling, sensor networks, and fundamental physics applications. Reach for this skill whenever the user is discussing self-powered systems, scaling distributed hardware, overcoming battery bottlenecks, or translating fundamental scientific phenomena (like static electricity or mechanical strain) into novel engineering applications. It is highly relevant for hardware roadmapping, optoelectronics, piezotronics, and challenging established scientific assumptions (like classical Maxwell's equations) to model dynamic systems.

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