「hie」の検索結果

Think and work like an expert Molecular Ecologist. Use when a task calls for Molecular Ecologist judgment. Reasons from population genetics, eDNA/metabarcoding, and marker choice (microsatellites, SNPs, mtDNA); analyzes with STRUCTURE/ADMIXTURE, hierfstat FST, DADA2 pipelines, and ddPCR; treats null alleles, Wahlund effect, batch effects, and eDNA allelic dropout as first-class failure modes.

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Think and work like an expert Life-Cycle Assessment Analyst. Use when a task calls for Life-Cycle Assessment Analyst judgment. Reasons from functional unit, attributional-versus-consequential framing, and ISO 14044 allocation hierarchy through openLCA, SimaPro, Brightway2, ecoinvent, and LCIA methods like TRACI and EF 3.0 while treating allocation-driven ranking flips, biogenic-versus-fossil carbon mistagging, cut-off-masked hotspots, and PCR mismatch as first-class failure modes.

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Think and work like an expert Hematologist. Use when a task calls for Hematologist judgment. Reasons from hematopoietic hierarchy, clonal evolution, and hemostatic balance through peripheral smear review, reticulocyte production index, flow cytometry, mixing studies, and WHO/ICC-anchored NGS and cytogenetics, while treating pseudothrombocytopenia, preanalytic line-draw and EDTA artifacts, and missed consumptive emergencies like TTP and DIC as first-class failure modes.

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Think and work like an expert Database Systems Researcher. Use when a task calls for Database Systems Researcher judgment. Reasons from storage hierarchy, concurrency semantics, query-optimization theory, and declared workload models through TPC-C/H, YCSB, and JOB benchmarks, Jepsen/Elle correctness checkers, and perf/blktrace/fio profiling while treating cardinality-estimation plan regressions, tail-latency spikes under skew, unfair fsync-disabled speedups, and benchmark-trick wins as first-class failure modes.

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Think and work like an expert Cryptography Engineer. Use when a task calls for Cryptography Engineer judgment. Reasons from explicit threat models, vetted primitives, key hierarchy, and constant-time secret handling through STRIDE threat modeling, standards (RFC 8446 TLS 1.3, FIPS 203/204, Ed25519), test vectors (Wycheproof, NIST CAVP), and protocol verifiers (Tamarin, ProVerif) while treating nonce reuse in AEAD, padding/Bleichenbacher oracles, timing side channels, and weak-RNG keys as first-class failure modes.

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Think and work like an expert Biomedical Engineer. Use when a task calls for Biomedical Engineer judgment. Reasons from ISO 14971 risk management, ISO 10993 biocompatibility matrices, ASTM F/ISO 14242 mechanical and wear testing, and FDA 510(k) substantial equivalence; treats stress shielding, UHMWPE osteolysis, F2129 corrosion artifacts, and predicate/material mismatches as first-class failure modes.

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Think and work like an expert Chemical Engineer. Use when a task calls for Chemical Engineer judgment. Reasons from closing mass, energy, and momentum balances and competing equilibrium/kinetics/transport regimes through Aspen Plus/HYSYS flowsheeting, McCabe-Thiele and Damkohler-based sizing, pinch analysis, and HAZOP/LOPA with API 520/521 relief, while treating azeotrope-pinched columns, reactor runaway, recycle impurity accumulation, and pump cavitation (NPSHa<NPSHr) as first-class failure modes.

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Think and work like an expert Bayesian Statistician. Use when a task calls for Bayesian Statistician judgment. Reasons from Bayes' rule, coherent uncertainty, exchangeability, and partial-pooling hierarchy through Stan/PyMC HMC-NUTS fits, prior and posterior predictive checks, PSIS-LOO, and SBC calibration while treating divergent transitions and funnels, weak identifiability and label switching, improper posteriors, and post-hoc prior tuning as first-class failure modes.

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Think and work like an expert Aerospace Engineer. Use when a task calls for Aerospace Engineer judgment. Reasons from margin-managed factors of safety, mass properties, and the analysis-test-similarity V&V hierarchy through FUN3D/SU2 CFD, NASTRAN/Abaqus FEA, JSBSim/Simulink 6-DOF, and FAR/CS, DO-178C, and NASA-STD compliance while treating flutter, buckling, inlet distortion, mass growth, and single-point failures as first-class failure modes.

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Think and work like an expert Atomic, Molecular & Optical Physicist. Use when a task calls for Atomic, Molecular & Optical Physicist judgment. Reasons from Rabi/OBE dynamics, laser-cooling hierarchy, optical lattices and Hubbard U/J, and magic-wavelength clock budgets through NIST ASD, ARC, QuTiP/PyLCP, and in-situ lattice-depth calibration while treating power-based depth guesses, polarization impurities, BBR shifts, and imaging-heating conflation as first-class failure modes.

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Generate structured feature specifications through a collaborative product interview. Acts as a senior PM and business analyst pair — arrives with a point of view, challenges scope, proposes options at every decision. Composes the requirement-quality atom for spec quality enforcement and collaborative-judgment for surfacing genuine decisions. Produces an epic/feature hierarchy in .lattice/requirements/ that serves as direct input to design-blueprint. Use when the user says 'forge requirements', 'write requirements', 'spec this feature', 'create a feature spec', 'define this epic', 'write a PRD', 'spec out what we are building', or 'requirement forge'.

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Grounded in first principles, rigorously examine and refine a user's plan, task, decision, goal, strategy, proposal, or idea through structured, progressively deeper questioning, in order to bridge the gap between the User and the Agent. Use when the user explicitly requests grilling, challenge, pressure-testing, cross-examination, red-team review, pre-mortem analysis, or a decision audit. The goal is to uncover unclear objectives, hidden assumptions, contradictions, weak evidence, missing information, overlooked constraints, dependencies, risks, trade-offs, failure modes, and misalignment between intended outcomes and likely real-world results. Begin by establishing a shared understanding of the user's actual intent, goals, constraints, and success criteria. Ask focused, high-leverage questions rather than broad or repetitive ones. Adapt each question based on previous answers, probing deeper where uncertainty, unsupported assumptions, or strategic weaknesses remain. Regularly summarize the current understanding of the user's intent and position to confirm alignment, expose misunderstandings, and refine the problem or goal definition. Distinguish facts, assumptions, hypotheses, and unknowns. Challenge reasoning rigorously while remaining constructive, respectful, and solution-oriented. Continue until the reasoning is internally coherent, evidence-aware, constraint-conscious, risk-assessed, and translated into a clearer, more actionable goal, decision, or plan. Ultimately, achieving the super-alignment.

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Provider-independent title design and kinetic typography direction for video, animation, ads, explainers, social hooks, brand films, lyric/text videos, title cards, main titles, lower thirds, captions-as-design, and other motion-led text. Use when an agent must plan, prompt, implement, hand off, iterate, or QA typography hierarchy, readability, timing, reveal/hold/exit, motion semantics, line breaks, safe areas, localization, brand constraints, accessibility, flashing/motion safety, or production specs for animated text.

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Assesses genetic health of populations for conservation using effective population size estimation (GONE2 for recent Ne trajectory, NeEstimator for contemporary Ne, Stairway Plot 2 and PSMC for historical Ne), F-statistics (hierfstat), runs of homozygosity (detectRUNS), and genetic diversity metrics. Use when estimating effective population size, detecting inbreeding or bottlenecks, or assessing genetic diversity in threatened species from microsatellite or SNP data.

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Infer orthologous genes and gene families across species using OrthoFinder3 (HOG-based phylogenetic orthology), SonicParanoid2, Broccoli, ProteinOrtho, OMA / FastOMA hierarchical orthologous groups, eggNOG-mapper, JustOrthologs, and TOGA whole-genome-alignment orthology. Use when building single-copy ortholog sets for phylogenomics, classifying co-orthologs and in/out-paralogs after gene duplication, propagating functional annotation via orthology with awareness of the ortholog conjecture, distinguishing speciation from duplication via gene-tree species-tree reconciliation, computing Quest-for-Orthologs benchmark performance, or running synteny-aware ortholog detection in WGD-affected lineages.

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Bulk-query Ensembl BioMart (and other BioMart instances) for cross-database ID mapping, gene/transcript/exon coordinates, and ortholog tables. Use when batch-converting Ensembl IDs to other namespaces (HGNC, RefSeq, UniProt, Entrez), pulling gene coordinate tables for thousands of genes, building ortholog wide-tables across species, or replacing slow Ensembl REST loops with one-shot bulk export. Encodes BioMart's XML query format, R biomaRt vs Python pybiomart trade-off, mart-vs-dataset hierarchy, and the URL endpoint that's BioMart-specific (separate from rest.ensembl.org).

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Designs Bayesian clinical trials including Phase I dose-finding (BOIN, CRM, EWOC, mTPI-2), meta-analytic-predictive (MAP) priors with robust mixtures for external data borrowing, EXNEX for basket trials, hierarchical models for safety AE (Berry-Berry), Bayesian platform trials (I-SPY 2, GBM AGILE, REMAP-CAP), and posterior probability stopping rules. Covers FDA Bayesian Devices Guidance (2010), FDA Bayesian Methodology in Drugs Draft (January 2026), BOIN Fit-for-Purpose qualification (December 2021), and Project Optimus dose-optimisation. Use when designing dose-finding studies, platform trials, or sensitivity analyses with informative priors.

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Proteina-Complexa flow-based protein backbone generation with fold-conditioned sampling guidance. Use this skill when: (1) Generating de novo protein backbones with hierarchical fold conditioning, (2) Exploring long-chain backbone generation beyond standard diffusion baselines, (3) Using NVIDIA Proteina-style flow matching workflows for controllable backbone design, (4) Comparing flow-based backbone generation against RFdiffusion or BoltzGen, (5) Prototyping fold-guided backbone campaigns before sequence design. This skill is based on the public NVIDIA Digital Bio Proteina project and uses "Proteina-Complexa" as the BioClaw-facing skill label. For sequence design after backbone generation, use proteinmpnn or solublempnn. For QC thresholds, use protein-design-qc.

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Implement complete dark mode for any frontend project. Auto-detects theme system (Flutter ThemeData, Tailwind dark class, CSS variables, MUI, Chakra UI, styled-components), generates a dark color palette with proper surface elevation hierarchy and desaturated brand colors, creates a theme toggle with system preference detection and persistence, migrates all hardcoded colors to theme tokens, handles special cases like images, shadows, form inputs, and charts, then verifies WCAG AA contrast ratios for both modes. Use when you need to add dark mode, fix dark theme contrast issues, create a theme switcher, or migrate hardcoded colors to theme-aware tokens.

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Use when the user wants to design, redesign, shape, critique, audit, polish, clarify, distill, harden, optimize, adapt, animate, colorize, extract, or otherwise improve a frontend interface. Covers websites, landing pages, dashboards, product UI, app shells, components, forms, settings, onboarding, and empty states. Handles UX review, visual hierarchy, information architecture, cognitive load, accessibility, performance, responsive behavior, theming, anti-patterns, typography, fonts, spacing, layout, alignment, color, motion, micro-interactions, UX copy, error states, edge cases, i18n, and reusable design systems or tokens. Also use for bland designs that need to become bolder or more delightful, loud designs that should become quieter, live browser iteration on UI elements, or ambitious visual effects that should feel technically extraordinary. Not for backend-only or non-UI tasks.

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Use Grok 4.5 as the required external design advisor when a task needs UI critique, UX critique, component-choice review, interaction-flow review, design imagery markdown, art direction, visual hierarchy judgment, design-system fit, color/type/layout suggestions, HTML mockups, SVG icons, handwritten SVG wordmarks, or file-based feedback on existing UI. Trigger on requests like "design a page", "generate design imagery", "give design advice", "optimize this UI", "improve UX", "optimize user flow", "review interaction", "check usability", "reduce friction", "choose the right component", "review this design", "create an icon", "suggest colors", "UI mockup", "visual direction", "lettering", "wordmark", "handwritten logo", or when another agent needs a second opinion on visual or interaction quality.

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Expert in CrewAI - the leading role-based multi-agent framework used by 60% of Fortune 500 companies. Covers agent design with roles and goals, task definition, crew orchestration, process types (sequential, hierarchical, parallel), memory systems, and flows for complex workflows. Essential for building collaborative AI agent teams. Use when: crewai, multi-agent team, agent roles, crew of agents, role-based agents.

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Multi-agent orchestration framework for autonomous AI collaboration. Use when building teams of specialized agents working together on complex tasks, when you need role-based agent collaboration with memory, or for production workflows requiring sequential/hierarchical execution. Built without LangChain dependencies for lean, fast execution.

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BMW's corporate site — distinct from BMW M's motorsport-bombastic variant, this is a measured and settled corporate-automotive interface. On a light (cream-tinted white) canvas, BMW corporate blue (#1c69d4) carries every primary CTA; dark navy hero bands frame model photography. BMW Type Next Latin sets the entire hierarchy on two weights — heavy 700 display and Light 300 body. Configuration and reservation flows ride a card-based 4-up grid, where each card holds a model render, a name, and a "Learn More" link.

日本語の概要は準備中です。原文の説明を表示しています。