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計算化学

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25,177件の結果

ruview-advanced-sensing

ソースruvnet/RuView/plugins/ruview/skills/ruview-advanced-sensing/SKILL.md
更新日

Advanced RuView capabilities — RuvSense multistatic sensing (attention-weighted fusion, geometric diversity, persistent field model), cross-viewpoint fusion across multiple nodes, RF tomography (ISTA L1 solver, voxel grids), longitudinal biomechanics drift, pre-movement intention signals, adversarial signal detection, and multistatic mesh security hardening. Use for research-grade or multi-node deployments.

Skill コンテンツの言語： 英語

ruview-applications

ソースruvnet/RuView/plugins/ruview/skills/ruview-applications/SKILL.md
更新日

Run RuView sensing applications — presence/occupancy, breathing & heart rate, activity & fall detection, 17-keypoint pose estimation (WiFlow), sleep monitoring & apnea screening, environment mapping, Mass Casualty Assessment (MAT), and the 3D point-cloud fusion demo. Use when someone wants to actually *do* something with a working RuView setup.

Skill コンテンツの言語： 英語

ruview-mmwave

ソースruvnet/RuView/plugins/ruview/skills/ruview-mmwave/SKILL.md
更新日

Set up and run RuView mmWave / FMCW radar sensing — ESP32-C6 + Seeed MR60BHA2 (60 GHz, heart rate / breathing rate / presence) and HLK-LD2410 (24 GHz, presence + distance), plus mmWave↔WiFi-CSI sensor fusion (48-byte fused vitals, MR60BHA2/LD2410 auto-detect, v0.5.0+). Use when the deployment includes a millimetre-wave radar alongside or instead of WiFi CSI.

Skill コンテンツの言語： 英語

adaptyv

ソースK-Dense-AI/scientific-agent-skills/skills/adaptyv/SKILL.md
更新日

Uses the Adaptyv Bio Foundry API and Python SDK to design protein characterization experiments, estimate costs, submit sequences, monitor laboratory progress, and retrieve results. Applies to Adaptyv Foundry, its target catalog, binding screening and affinity assays, thermostability, expression, fluorescence, epitope binning, and enzyme activity workflows, including code using adaptyv or FoundryClient.

Skill コンテンツの言語： 英語

mageck

ソースK-Dense-AI/scientific-agent-skills/skills/mageck/SKILL.md
更新日

Analyzes pooled CRISPR screen FASTQ reads and guide-count matrices with MAGeCK, validates guide libraries and contrasts, measures replicate and library QC, and produces gene hit rankings with effect sizes and FDR. Use for new knockout, CRISPRi, or CRISPRa screen analysis, enrichment or depletion contrasts, and MAGeCK count/test workflows; existing public dependency-score lookup belongs to DepMap.

Skill コンテンツの言語： 英語

openpiv

ソースK-Dense-AI/scientific-agent-skills/skills/openpiv/SKILL.md
更新日

Performs Particle Image Velocimetry (PIV) analysis with OpenPIV. Use when extracting velocity fields from PIV image pairs, analyzing fluid dynamics or flow visualization experiments, cross-correlating interrogation windows, validating and replacing spurious PIV vectors, or computing vorticity, strain rate, and turbulence statistics from measured velocity fields.

Skill コンテンツの言語： 英語

pkpd-modeling

ソースK-Dense-AI/scientific-agent-skills/skills/pkpd-modeling/SKILL.md
更新日

Pharmacokinetic and pharmacodynamic modelling and simulation - non-compartmental analysis, compartmental and population PK, PK/PD and exposure-response, TMDD, PBPK orientation, bioequivalence, allometric scaling and first-in-human dose, drug interaction prediction, and Bayesian therapeutic drug monitoring. Use when analysing concentration-time data, deriving exposure metrics, fitting PK or PD models, or evaluating dosing regimens. Triggers include "pharmacokinetics", "pharmacodynamics", "PK/PD", "NCA", "non-compartmental", "AUC", "Cmax", "lambda z", "half-life", "clearance", "volume of distribution", "compartmental model", "population PK", "popPK", "NONMEM", "nlmixr2", "Pharmpy", "Monolix", "exposure-response", "Emax", "EC50", "indirect response", "effect compartment", "TMDD", "PBPK", "bioequivalence", "RSABE", "ABEL", "allometric scaling", "first-in-human", "MABEL", "drug-drug interaction", "DDI", "ICH M12", "concentration-QTc", "therapeutic drug monitoring", "MIPD", and "dosing regimen".

Skill コンテンツの言語： 英語

primer-design

ソースK-Dense-AI/scientific-agent-skills/skills/primer-design/SKILL.md
更新日

Designs and audits PCR and RT-qPCR primers with Primer3, explicit thermodynamic conditions, reference-based off-target amplification searches, and traceable sequence coordinates. Use for designing primer pairs, checking existing primers, exon-junction or isoform-specific assays, variant masking, cloning tails, multiplex compatibility, and interpreting Primer-BLAST results. Includes bounded local in-silico PCR and BLAST screening; distinguishes computational candidates from experimentally validated assays.

Skill コンテンツの言語： 英語

rowan

ソースK-Dense-AI/scientific-agent-skills/skills/rowan/SKILL.md
更新日

Rowan is a cloud-native molecular modeling and medicinal-chemistry workflow platform with a Python API. Use for pKa and macropKa prediction, conformer and tautomer ensembles, docking and analogue docking, protein-ligand cofolding, MSA generation, molecular dynamics, permeability, descriptor workflows, and related small-molecule or protein modeling tasks. Ideal for programmatic batch screening, multi-step chemistry pipelines, and workflows that would otherwise require maintaining local HPC/GPU infrastructure.

Skill コンテンツの言語： 英語

tellurium

ソースK-Dense-AI/scientific-agent-skills/skills/tellurium/SKILL.md
更新日

Simulates biochemical kinetic models from SBML or Antimony with Tellurium and libRoadRunner, checks model units, compares deterministic parameter perturbations, and exports and replays SBML plus SED-ML COMBINE archives. Use for reaction-network time courses, kinetic parameters, concentration dynamics and reproducible simulation experiments; steady-state constraint-based metabolic flux analysis belongs to cobrapy.

Skill コンテンツの言語： 英語

pixijs-scene-particle-container

ソースpixijs/pixijs/skills/pixijs-scene-particle-container/SKILL.md
更新日

Use this skill when rendering thousands of lightweight sprites in PixiJS v8. Covers ParticleContainer with Particle instances, addParticle/removeParticle, particleChildren array, dynamicProperties (vertex, position, rotation, uvs, color), boundsArea, roundPixels, update, inherited alpha/tint/blendMode from ancestors. Triggers on: ParticleContainer, Particle, IParticle, addParticle, particleChildren, dynamicProperties, boundsArea, particle effects, particle alpha, particle tint, fade particles, constructor options, ParticleContainerOptions, ParticleOptions.

Skill コンテンツの言語： 英語

math-olympiad

ソースanthropics/claude-plugins-official/plugins/math-olympiad/skills/math-olympiad/SKILL.md
更新日

Solve competition math problems (IMO, Putnam, USAMO, AIME) with adversarial verification that catches the errors self-verification misses. Activates when asked to 'solve this IMO problem', 'prove this olympiad inequality', 'verify this competition proof', 'find a counterexample', 'is this proof correct', or for any problem with 'IMO', 'Putnam', 'USAMO', 'olympiad', or 'competition math' in it. Uses pure reasoning (no tools) — then a fresh-context adversarial verifier attacks the proof using specific failure patterns, not generic 'check logic'. Outputs calibrated confidence — will say 'no confident solution' rather than bluff. If LaTeX is available, produces a clean PDF after verification passes.

Skill コンテンツの言語： 英語

analyzing-campaign-attribution-evidence

ソースmukul975/Anthropic-Cybersecurity-Skills/skills/analyzing-campaign-attribution-evidence/SKILL.md
更新日

Systematically evaluate cyber-campaign evidence to attribute an operation to a threat actor, using the Diamond Model and Analysis of Competing Hypotheses (ACH) to weigh infrastructure overlaps, TTP consistency, malware code similarity, and timing/language artifacts into confidence-weighted attribution assessments. Use when an incident investigation needs a defensible attribution confidence level.

Skill コンテンツの言語： 英語

assessing-vector-and-embedding-weaknesses

ソースmukul975/Anthropic-Cybersecurity-Skills/skills/assessing-vector-and-embedding-weaknesses/SKILL.md
更新日

Test RAG vector stores (Pinecone, Qdrant, Weaviate, Chroma, pgvector, FAISS) for embedding inversion, cross-tenant data leakage, and data poisoning per OWASP LLM08:2025. Use when performing an authorized security assessment of a RAG pipeline's retrieval layer or auditing multi-tenant vector-store isolation.

Skill コンテンツの言語： 英語