Think and work like an expert Earthquake Engineer. Use when a task calls for Earthquake Engineer judgment. Reasons from ASCE 7 DRS and SDC, capacity design (R, Cd, Ω₀), ELF/MRS/NRHA and ASCE 41 pushover; models in SAP2000/ETABS/OpenSees with PEER NGA-West2 motions; treats liquefaction, soft-story P-delta collapse, and record-scaling artifacts as first-class failure modes.
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。
K-Dense-AI/scientific-agents☆ 2082026年10月3日 更新
Think and work like an expert Ecotoxicologist. Use when a task calls for Ecotoxicologist judgment. Reasons from bioavailability (BLM/WHAM), OECD 201–222 tiered tests, and ECx/SSD HC5–PNEC derivation; compares PEC/PNEC under REACH/PPP frames while treating third-phase BCF artifacts, mixture CA departures, and mesocosm exposure mismatch as first-class failure modes.
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。
K-Dense-AI/scientific-agents☆ 2082026年10月3日 更新
Think and work like an expert Dynamical Systems Theorist. Use when a task calls for Dynamical Systems Theorist judgment. Reasons from state spaces, invariant sets, bifurcations, and multiple time scales through normal-form classification, center-manifold reduction, Floquet/Poincaré maps, and continuation tools like AUTO, MatCont, and DynamicalSystems.jl while treating spurious chaos from finite-time Lyapunov bias, false limit cycles mistaken for tori, numerical blow-up versus true singularity, and Takens embedding artifacts as first-class failure modes.
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。
K-Dense-AI/scientific-agents☆ 2082026年10月3日 更新
Think and work like an expert Ecologist. Use when a task calls for Ecologist judgment. Reasons from Preston/Fisher SADs and Hutchinson fundamental vs realized niches; designs quadrat/transect and distance/occupancy surveys; filters GBIF issue flags and iNaturalist DQA; fits vegan/iNEXT/unmarked GLMMs with Moran's I and nlme/glmmTMB spatial correlation while treating pseudoreplication, effort bias, and citizen-science artifacts as first-class failure modes.
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。
K-Dense-AI/scientific-agents☆ 2082026年10月3日 更新
Think and work like an expert Computational Chemist. Use when a task calls for Computational Chemist judgment. Reasons from Kohn–Sham DFT, def2/D4 functional selection, and conformer ensembles through VASP/Gaussian/ORCA, AMBER/GROMACS MD, CREST/CENSO sampling, ONIOM/QM/MM electrostatic embedding, GMTKN55 validation, and SCF convergence escalation while treating B3LYP/6-31G*, BSSE, link-atom artifacts, and force-field mismatch as first-class failure modes.
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。
K-Dense-AI/scientific-agents☆ 2082026年10月3日 更新
Think and work like an expert Condensed Matter Physicist. Use when a task calls for Condensed Matter Physicist judgment. Reasons from Bloch bands, quasiparticles, and symmetry through ARPES/STM/neutron/transport workflows, VASP/QE/Wannier90/DMFT, and Materials Project/ICSD/MPDS while treating matrix-element artifacts, Mott vs. DFT gaps, pseudogap vs. SC gap, and Planckian bad-metal transport as first-class failure modes.
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。
K-Dense-AI/scientific-agents☆ 2082026年10月3日 更新
Think and work like an expert Comparative Physiologist. Use when a task calls for Comparative Physiologist judgment. Reason from the Krogh principle and oxygen cascade through intermittent-flow respirometry, SMR/BMR/MMR scope, Q10 and heterothermy, hemoglobin P50, allometry and PGLS, while treating chamber drift, activity artifacts, phylogenetic pseudoreplication, and SMR definition mismatch as first-class failure modes.
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。
K-Dense-AI/scientific-agents☆ 2082026年10月3日 更新
Think and work like an expert Digital Pathology Scientist. Use when a task calls for Digital Pathology Scientist judgment. Reasons from whole-slide pixels, pathologist-ground-truth label levels, and stain/scanner batch effects through QuPath, CLAM/TIAToolbox MIL, Macenko/Vahadane normalization, and MI-CLAIM/TRIPOD+AI standards while treating patch-level leakage, scanner-ID shortcuts, attention-on-necrosis artifacts, and inter-pathologist-kappa ceilings as first-class failure modes.
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。
K-Dense-AI/scientific-agents☆ 2082026年10月3日 更新
Think and work like an expert Differential Geometer. Use when a task calls for Differential Geometer judgment. Reasons from connections, curvature, and holonomy; fixes Lee vs Besse/MTW Riemann signs; uses SageManifolds/xAct/Cadabra, Chern–Weil and Atiyah–Singer index theory, and model-space checks (S^n, flat tori) while treating chart artifacts, torsion misuse, and CAS convention drift as first-class failure modes.
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。
K-Dense-AI/scientific-agents☆ 2082026年10月3日 更新
Think and work like an expert Biophysicist. Use when a task calls for Biophysicist judgment. Reasons from energy landscapes, kT-scale thermodynamics, conformational ensembles, and the equilibrium-versus-kinetics distinction through smFRET, optical/magnetic tweezers, patch clamp, cryo-EM, and MD with force-field validation while treating photobleaching and blinking, FRET crosstalk, tether and series-resistance artifacts, and sampling or force-field bias as first-class failure modes.
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。
K-Dense-AI/scientific-agents☆ 2082026年10月3日 更新
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.
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。
K-Dense-AI/scientific-agents☆ 2082026年10月3日 更新
Think and work like an expert Cancer Biologist. Use when a task calls for Cancer Biologist judgment. Reasons from hallmark capabilities, clonal evolution, and TME context; separates driver from passenger, cell-autonomous from stromal mechanisms, and 2D artifacts from PDO/PDX-validated dependencies using TCGA, DepMap, OncoKB, and REMARK-grade biomarker logic.
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。
K-Dense-AI/scientific-agents☆ 2082026年10月3日 更新
Think and work like an expert Chemical Biologist. Use when a task calls for Chemical Biologist judgment. Reasons from chemical genetics, ABPP/TPP/CETSA chemoproteomics, and SGC/Portal probe criteria; deconvolves phenotypic hits with PAINS/aggregator triage, inactive analogs, and genetic epistasis while treating colloidal aggregation, probe promiscuity, and degrader DC50/Dmax tag artifacts as first-class failure modes.
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。
K-Dense-AI/scientific-agents☆ 2082026年10月3日 更新
Think and work like an expert Cell Signaling Biologist. Use when a task calls for Cell Signaling Biologist judgment. Reasons from RTK–RAS–MAPK and PI3K–Akt–mTOR phosphorylation networks, pathway crosstalk and feedback; validates with phospho-Western, phospho-flow, and PhosphoSitePlus while treating serum-starvation artifacts, inhibitor off-targets, and RNA footprint vs PTM mismatch as first-class failure modes.
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。
K-Dense-AI/scientific-agents☆ 2082026年10月3日 更新
Think and work like an expert Biomaterials Scientist. Use when a task calls for Biomaterials Scientist judgment. Reasons from material-biology interfaces, degradation-product toxicity, and mechanical mismatch to host tissue through ISO 10993 biological evaluation plans, ISO 10993-12 extract conditions, GPC/ICP/SEM characterization, and sterilization validation while treating endotoxin contamination, pH shift from acidic degradation, extract-ratio artifacts, and non-final-form test articles as first-class failure modes.
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。
K-Dense-AI/scientific-agents☆ 2082026年10月3日 更新
Think and work like an expert Agroecologist. Use when a task calls for Agroecologist judgment. Reasons from socio-ecological farm systems, functional diversity, soil-biology-mediated fertility, and yield-service trade-offs through mother-baby and mixed-model trials, N/P/C mass balances, PLFA/amplicon and pollinator surveys, and NDVI/FRAGSTATS landscape analysis, while treating edge-effect and plot-size artifacts, weather-year confounding, surface-only soil carbon, and ignored labor/tenure adoption constraints as first-class failure modes.
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。
K-Dense-AI/scientific-agents☆ 2082026年10月3日 更新
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.
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。
K-Dense-AI/scientific-agents☆ 2082026年10月3日 更新
Think and work like an expert Anatomist. Use when a task calls for Anatomist judgment. Reasons from homology, EPB, and von Baer principles through gross dissection, diceCT/μCT/MRI pipelines, UBERON–PATO EQ annotation, MorphoSource/oVert digitization, geometric morphometrics, and NAV/TA2 nomenclature while treating fixation shrinkage, segmentation artifacts, landmark homology error, and collection bias as first-class failure modes.
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。
K-Dense-AI/scientific-agents☆ 2082026年10月3日 更新
Think and work like an expert Bioinformatician. Use when a task calls for Bioinformatician judgment. Reference-build discipline (GRCh38/GENCODE/Ensembl, MANE), batch-as-covariate DE (DESeq2/edgeR), index hopping/UDI, GATK/BQSR/PLINK GWAS multiplicity, nf-core reproducibility, and scRNA-seq ambient-RNA/doublet artifacts.
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。
K-Dense-AI/scientific-agents☆ 2082026年10月3日 更新
Content-Derived Design — reads existing HTML and writes a stronger standalone page from headings, facts, names, dates, numbers, links, emails, and colors already in that file. CLI: npx reimagine-it --auto -i page.html -o out.html; also variations, lock, and audit. Use when the user says /reimagine-it, "reimagine it", "reinvent this", "redesign this page", "make an infographic", wants a content-aware redesign or a visual leap instead of a mood board. All 17 tokens: webpage, infographic, svg, 3js, simulation, artistic, cinematic, dashboard, photography, landing, editorial, gradient, showcase, motion, glass, lookbook, particles — plus leftover words as a brief. Also /reimagine-it audit for quality checks. The agent runs the CLI; it does not hand-author the page. Installed via npx skills add Kayforkind/reimagine-it or plugin marketplace. Not /better. Not a mood board. Does not ingest PDF, PPTX, or DOCX.
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。
Kayforkind/reimagine-it☆ 2072026年10月10日 更新
Emit the content signals reimagine-it reads from an HTML file — title, anchors, proper nouns, dates, numbers, emails, links, source hex colors, and the derived palette — as JSON without generating a redesign. Use when the user says /reimagine-it extract, "what does the engine see in this page", "extract the palette", "pull the facts from this page", or wants content analysis for research, migration, or design-system work. CLI: npx reimagine-it extract -i page.html -o signals.json. Part of the reimagine-it Content-Derived Design suite.
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。
Kayforkind/reimagine-it☆ 2072026年10月10日 更新
Content-derived infographic poster — reads the source file and builds a statistical poster from the facts already in it. Not a dashboard, not a CV, not an AntV template. Uses common-scale encodings (Cleveland–McGill floor), ISOTYPE unit counts (Neurath), custom data glyphs (Lupi/Fragapane), and a lossless data table. Palette, glyphs, and composition are derived from the source's own content. No pies, donuts, gauges, 3D charts, or fabricated KPIs. Part of the reimagine-it Content-Derived Design suite.
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。
Kayforkind/reimagine-it☆ 2072026年10月10日 更新
Author the research plan — fundamentals first, trade ideas last; Constitution Check evaluated twice; Deviation Register with mandatory Expiry; emits the four side artifacts (brief/entities/reproduce/contracts). Technical (market_data_stage: early) theses MUST emit the entities.md bars schema before implement (Q42).
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。
agentii-ai/agentii-investment-intelligence☆ 2062026年9月29日 更新
Thesis report synthesis — turn a thesis's markdown artifacts into its letter-size thesis-report.html, then OPTIMIZE it against real page renders. Four-step loop — pack (deterministic Python bundle of all sources + report/metrics.json), author (the LLM writes report/content.html — narrative, KPI tiles, badges, timeline, tables and citations are LLM judgment), assemble (deterministic validation, template injection, Q50 pins, Q47 overflow gate), render + optimize (Chrome headless per-page PNGs — the LLM reads them and iterates until every page is visually clean). Spec 046 Q46–Q50.
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。
agentii-ai/agentii-investment-intelligence☆ 2062026年9月29日 更新