Results for “dynamics”

Classical and modern physics expert covering mechanics, electromagnetism, thermodynamics, quantum mechanics, and relativity

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Research and ideation partner for GAME DESIGN — think through design ideas before writing them into the GDD; produces a brief, never edits the GDD itself. Use to assess a genre or market for viability, dissect a reference game (mechanics → dynamics → aesthetics), explore how to improve or extend an existing system, flow, or content type, research new mechanics the design lacks, investigate a part of the GDD in code, or develop the research bucket of a /unikit-gd-review report into decided edits. Trigger on "explore how to improve the flow", "ways to improve the combat system", "is this genre saturated", "break down the combat of Hades", "work out the review's open questions". GAME-DESIGN research only — for CODE or technical research use /unikit-explore; to reconstruct a design from code use /unikit-gd-recon; to write a change into the GDD use /unikit-gd-system or /unikit-gd-spec; to apply edits you know use /unikit-gd-apply; to invent a new game use /unikit-gd-brainstorm.

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Author and own one flow's design document (the FLOW.md objective flow) at .unikit/gamedesign/flows/FLOW-<slug>.md — the dynamics layer of the GDD (what the player does over time). Create the skeleton and walk the collaborative section-cycle to write its objectives, pacing, dependencies, and funnel events ("design the first-session flow", "map the onboarding sequence", "write the FLOW for the boss encounter"), AND revise it after approval under the delta discipline ("retune the pacing", "add a branch", "change a GOAL", "rework the onboarding") — a cue/number change is Tuning, a small step change a Tweak, restructuring a Rework; each bumps the version and logs the delta. Selects the wiring mode (linear | conditional | emergent) and re-renders the ## Flow Map [gen] / ## Funnel [gen] blocks in GAME.md. To add or detail a system use /unikit-gd-system; to edit GAME.md content use /unikit-gd-spec; to apply a multi-zone edit use /unikit-gd-apply; for a new game concept use /unikit-gd-brainstorm.

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Meta-skill that orchestrates the discourse skill suite: routes between steel-man-argument, socratic-questioning, toulmin-argument-analysis, logical-fallacy-detector, bad-faith-rhetoric-detector, discourse-elision-analyzer, forensic-speech-structure, and productive-discourse-facilitator. Use when analyzing conversations, facilitating discourse, or operating as a dialogue copilot. Maintains mode (silent analysis, coaching overlay, active facilitator) and decides which skills to invoke based on conversation dynamics.

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Designs and analyzes in vivo CRISPR screens in animal tumor models, organoids, and immune-cell adoptive transfers. Covers bottleneck math (250x cells/sgRNA requires ~25M cells implanted; impossible for most syngeneic models, forcing focused libraries), focused library design (Manguso 2017 Nature 547:413 immune screen; Chen 2015 tumor screens), CRISPR-StAR intrinsic-control screening (Uijttewaal 2025 Nat Biotechnol 43:1848), clonal-dynamics-limited detection, tumor-explant DNA recovery, syngeneic vs xenograft vs PDX considerations, and the relationship to downstream MAGeCK / drugZ analysis. Use when designing in vivo CRISPR screens for tumor / immune / metastasis biology, choosing focused vs genome-wide for animal models, addressing bottleneck-induced clonal collapse, picking the syngeneic / xenograft / PDX model, integrating in vivo with in vitro results, or applying CRISPR-StAR for animal experiments.

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Corrects the gene-independent copy-number artifact in CRISPR-Cas9 screens (Aguirre 2016 / Munoz 2016 Cancer Discov) where amplified loci appear essential from DNA-damage burden of simultaneous cuts. Covers the gene-independent DNA-damage / G2-arrest mechanism, CRISPRcleanR (Iorio 2018) unsupervised pre-hoc correction, CERES (Meyers 2017) joint CN + gene-effect model, Chronos (Dempster 2021) DepMap-standard population-dynamics + CN model with lowest residual bias, the decision tree by data availability, the Spearman LFC-vs-CN diagnostic, focal-amplification examples (ERBB2 in HER2+, MYC in colorectal, FGFR1 in head and neck), and CRISPRi/a alternatives that bypass the artifact. Use when screening cancer cell lines, diagnosing essentiality at amplified loci, choosing CRISPRcleanR / CERES / Chronos, deciding whether CN correction is needed before MAGeCK / BAGEL2 / drugZ, or switching from Cas9 to CRISPRi.

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Expert-level process simulation covering Aspen Plus, HYSYS, steady state and dynamic simulation, thermodynamic model selection, and simulation troubleshooting.

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Expert-level exoplanet science covering detection methods, orbital dynamics, planetary atmospheres, habitability, and the search for biosignatures.

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Expert-level fluid mechanics covering fluid statics, continuity, Bernoulli, Navier-Stokes, boundary layers, turbulence, pipe flow, and external aerodynamics.

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Expert-level classical mechanics knowledge. Use when working with Newton's laws, kinematics, dynamics, energy, momentum, rotational motion, oscillations, gravitation, Lagrangian mechanics, or Hamiltonian mechanics. Also use when the user mentions 'force', 'torque', 'momentum', 'energy conservation', 'simple harmonic motion', 'projectile', 'friction', 'center of mass', 'moment of inertia', 'Lagrangian', or 'Hamiltonian'.

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Expert-level physical chemistry knowledge. Use when working with thermodynamics, chemical kinetics, quantum chemistry, statistical mechanics, spectroscopy, electrochemistry, or surface chemistry. Also use when the user mentions 'Gibbs energy', 'equilibrium constant', 'reaction kinetics', 'rate law', 'activation energy', 'Arrhenius', 'partition function', 'Schrodinger equation', 'molecular orbital', 'electrochemistry', 'Nernst equation', or 'surface adsorption'.

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Expert-level plasma physics knowledge. Use when working with plasma state, Debye shielding, plasma oscillations, magnetohydrodynamics, plasma confinement, fusion plasmas, space plasmas, plasma waves, or plasma instabilities. Also use when the user mentions 'plasma', 'Debye length', 'plasma frequency', 'MHD', 'magnetic confinement', 'tokamak', 'plasma instability', 'Alfven wave', 'Langmuir probe', 'ionosphere', or 'solar wind'.

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Expert-level fluid physics knowledge. Use when working with fluid statics, fluid dynamics, Bernoulli equation, viscosity, turbulence, Navier-Stokes equations, boundary layers, vorticity, compressible flow, or surface tension. Also use when the user mentions 'Bernoulli', 'Navier-Stokes', 'Reynolds number', 'turbulence', 'viscosity', 'boundary layer', 'vorticity', 'continuity equation', 'laminar flow', 'pressure', 'buoyancy', or 'surface tension'.

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Culture assessment and monitoring with three modes — Diagnostic for a deep session surfacing the gap between declared culture and actual culture, Review for periodic check-ins on whether behavior is shifting, and Alert Triggers for setting tripwires around culture-strategy misalignment, regression, and integration risk. Not a culture change programme — a mirror. Updates company-context.md after every run. Triggers on questions about culture, values, team dynamics, how decisions really get made, why change efforts stall, merger integration, or whether the organisation can actually execute its strategy. Based on practice by Eterdis (eterdis.com).

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Knowledge base from the GAO Agile Assessment Guide (GAO-24-105506, 2023). Use for assessing and managing Agile software development in federal programs: the Agile Manifesto and framework family (Scrum, Kanban, XP, SAFe, DA, DSDM, Lean, DevOps); the three adoption perspectives (team dynamics, program operations, organization environment); requirements decomposition (epics, features, user stories, INVEST, MoSCoW, definition of done); Agile-aware federal contracting (FAR, modular contracting, SOO/PWS/SOW, product owner vs. COR); program monitoring and control (WBS, cost, schedule, EVM at the feature level); Agile metrics (velocity, lead/cycle time, CFD, burn charts); and the auditor's key-question bank. Oversight- and acquisition-oriented: it tells you how to *assess and govern* Agile programs, not how to code. Thin on hands-on engineering practice, deep cost/schedule checklists (see gao-cost, gao-schedule), and any non-US-federal context.

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Research any open-source repository end to end and answer the core question — SHOULD YOU contribute to it? — with a GO / NO-GO / GO-IF verdict backed by evidence: snapshot, momentum, contribution landscape (PR acceptance rates, outside-contributor merge rates, first-timer outcomes), issue health, governance, community sentiment, and a final go/no-go recommendation. Use when the user asks 'should I contribute to X', wants a before-I-contribute due-diligence check on a project, asks whether a project accepts outside PRs, wants contribution-health numbers like PR merge rates or stale-PR counts, or asks for a deep dive on an open-source codebase's health and dynamics before investing time in it.

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Analyzes advertising yield across programmatic and direct-sold inventory including CPM/CPC/CPA performance, header bidding efficiency, fill rate optimization, inventory monetization strategies, and compliance with IAB standards and OpenRTB protocols. USE THIS SKILL WHEN: - You need to audit ad revenue performance or diagnose yield drops - Someone asks about header bidding configuration or Prebid.js optimization - You are analyzing fill rates, eCPM trends, or ad unit performance - A project involves programmatic advertising, SSP integration, or ad serving - You need to verify ads.txt, sellers.json, or supply chain compliance - Someone mentions CPM floors, bid density, or auction dynamics - You are evaluating ad quality controls, viewability, or ad-related UX impact - A codebase integrates Google Ad Manager, AdMob, Prebid, or any SSP TRIGGER PHRASES: "ad yield", "eCPM", "fill rate", "header bidding", "Prebid", "programmatic ads", "ad monetization", "CPM optimization", "ad revenue", "ads.txt", "ad serving", "SSP", "ad unit performance", "viewability"

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Sparse Identification of Nonlinear Dynamics (SINDy) — discover governing equations from time-series data. Builds sparse dynamical system models dx/dt = f(x) from measurements using PySINDy. Use when you have trajectory data and want to find the underlying ODE.

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Solve quantitative problems in biophysics — pharmacokinetics (PK volume of distribution, clearance, half-life), epidemiology (R0, attack rate), toxicology (LD50, NOAEL), population genetics (Hardy-Weinberg, Fst), enzyme kinetics (Michaelis-Menten), thermodynamics. Use for first-principles quantitative biology calculations, dose calculations, exposure assessment, and biophysical-property estimation.

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Solve ordinary differential equations (initial and boundary value problems). Supports stiff/non-stiff systems, event detection, Hamiltonian/symplectic integration, parameter sweeps, and phase space analysis. Use for any ODE system in physics, engineering, or applied math.

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Extract supplier invoice details structured for direct import into ERP systems like SAP, Oracle, or Microsoft Dynamics.

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Corrects the gene-independent copy-number artifact in CRISPR-Cas9 screens (Aguirre 2016 / Munoz 2016 Cancer Discov) where amplified loci appear essential from DNA-damage burden of simultaneous cuts. Covers the p53-dependent G2-arrest mechanism, CRISPRcleanR (Iorio 2018) unsupervised pre-hoc correction, CERES (Meyers 2017) joint CN + gene-effect model, Chronos (Dempster 2021) DepMap-standard population-dynamics + CN model with lowest residual bias, the decision tree by data availability, the Spearman LFC-vs-CN diagnostic, focal-amplification examples (ERBB2 in HER2+, MYC in colorectal, FGFR1 in head and neck), and CRISPRi/a alternatives that bypass the artifact. Use when screening cancer cell lines, diagnosing essentiality at amplified loci, choosing CRISPRcleanR / CERES / Chronos, deciding whether CN correction is needed before MAGeCK / BAGEL2 / drugZ, or switching from Cas9 to CRISPRi.

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Designs and analyzes in vivo CRISPR screens in animal tumor models, organoids, and immune-cell adoptive transfers. Covers bottleneck math (250x cells/sgRNA requires ~25M cells implanted; impossible for most syngeneic models, forcing focused libraries), focused library design (Manguso 2017 Nature 547:413 immune screen; Chen 2015 tumor screens), CRISPR-StAR intrinsic-control screening (Uijttewaal 2025 Nat Biotechnol 43:1848), clonal-dynamics-limited detection, tumor-explant DNA recovery, syngeneic vs xenograft vs PDX considerations, and the relationship to downstream MAGeCK / drugZ analysis. Use when designing in vivo CRISPR screens for tumor / immune / metastasis biology, choosing focused vs genome-wide for animal models, addressing bottleneck-induced clonal collapse, picking the syngeneic / xenograft / PDX model, integrating in vivo with in vitro results, or applying CRISPR-StAR for animal experiments.

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Side-by-side competitive comparison of two or more companies. Use when user says "compare", "X vs Y", "which is better", or asks about competitive dynamics between specific companies.

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