Apple's approach to interface design and fluid, physical motion, translated for the web. Use when building or reviewing gesture-driven UI, spring animations, drag/swipe/sheet interactions, momentum and interruptible transitions, translucent materials and depth, typography (optical sizing, tracking, leading), reduced-motion, or the design foundations (feedback, spatial consistency, restraint) behind Apple-style interfaces.
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。
samuelpatro/.claude☆ 32026年9月3日 更新
Segment single cells from multiplexed IMC/MIBI tissue images using Mesmer/DeepCell, Cellpose, or ilastik+CellProfiler, covering whole-cell vs nuclear segmentation, the summed-membrane-channel decision, nuclear-expansion bias, lateral spillover, resolution-floor parameters, and downstream-proxy evaluation. Use when delineating cells after preprocessing, choosing a segmentation model, building a cell mask for quantification, diagnosing impossible double-positive populations, or troubleshooting over/under-segmentation.
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。
peacezha/HPClaw☆ 32026年10月11日 更新
Designs cytosine (CBE, C-to-T) and adenine (ABE, A-to-G) base-editor guides by positioning the target base at the activity-peak of the editing window (protospacer positions ~5-7, PAM-distal numbering), minimizing bystander edits for product purity, reading dinucleotide context (APOBEC1 TC favored / GC disfavored), and selecting the editor variant (BE4max, ABEmax, ABE8e, YE1/SECURE, TadCBE, CGBE, SpG/SpRY-BE). Covers knockout by premature stop (CRISPR-STOP/iSTOP) and splice-site disruption, the three off-target classes (Cas-dependent, Cas-independent DNA, RNA), outcome prediction (BE-Hive/DeepBE), and the base-vs-prime-vs-HDR decision. Use when installing a transition mutation without a double-strand break, knocking out a gene without indels, or choosing CBE vs ABE. Generic guide scoring, prime editing, and HDR donors are separate skills.
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。
peacezha/HPClaw☆ 32026年10月11日 更新
Simulate transcription factor perturbation effects on cell state in silico with CellOracle and Dynamo, and predict transcriptional responses to genetic perturbations with GEARS, scGen, and CPA. Covers the direction-not-magnitude principle, local-linear validity, the GRN/velocity error it inherits, baseline discipline (mean and additive baselines), and the validation gap. Use when predicting TF knockout or overexpression effects, ranking driver TFs for fate transitions, or planning perturbation experiments. For GRN construction see multiomics-grn; for experimental Perturb-seq see single-cell/perturb-seq.
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。
peacezha/HPClaw☆ 32026年10月11日 更新
Produce and interpret PCA, t-SNE, UMAP, and PHATE plots for high-dimensional omics data with rigor about which method preserves what (variance, local structure, manifold, transitions), hyperparameter sensitivity, and the well-documented limits of 2D embeddings. Covers PCA biplot/scree/loadings, t-SNE PCA initialization (Kobak-Berens 2019), UMAP n_neighbors/min_dist trade-offs, and the Chari-Pachter 2023 critique. Use when visualizing high-dimensional data — bulk PCA, single-cell embeddings, multi-omics integration projections.
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。
peacezha/HPClaw☆ 32026年10月11日 更新
Model gene-family birth-death dynamics across a species tree using CAFE5 (Mendes et al 2020 Bioinformatics 36:5516 gamma-distributed rate categories), CAFE5-error (annotation-error-aware), Count (Csurös 2010 ancestral state reconstruction), BadiRate (Librado 2012 likelihood + parsimony), DupliPHY-Family, and ALE/AleRax (for per-family DTL; see [[gene-tree-species-tree-reconciliation]]). Test lineage-specific gene-family expansions and contractions, distinguish biological dynamics from annotation artifacts, account for assembly fragmentation, identify functional enrichment in expanded / contracted families. Use when correlating gene-family changes with phenotype evolution, ranking lineages by adaptive gene-family-rate shifts, post-WGD dosage-balance analysis, or building Birth-death models from OrthoFinder presence/absence matrices.
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。
peacezha/HPClaw☆ 32026年10月11日 更新
Quantify homologous recombination deficiency (HRD) from tumor copy number using the three genomic-scar metrics — loss of heterozygosity (LOH), large-scale state transitions (LST), and telomeric allelic imbalance (TAI) — with scarHRD, and via the whole-genome HRDetect and CHORD models. Covers the genomic instability score, the PARP-inhibitor clinical context, whole-genome-doubling correction, and the scar-versus-state distinction. Use when computing an HRD score for PARP-inhibitor eligibility, deriving LOH/LST/TAI scars from allele-specific copy number, deciding between scar-based and mutational-signature HRD methods, or interpreting an HRD result in a BRCA-reverted or low-purity tumor.
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。
peacezha/HPClaw☆ 32026年10月11日 更新
Use this skill when selecting or replacing an ELD provider. Covers the FMCSA Registered ELD list, evaluation criteria, common provider removals from the registered list, and the 60-day transition rule.
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。
x3allamerican/skills☆ 32026年5月17日 更新
Use this skill when managing post-SAP follow-up testing for a driver. Covers the testing cadence, recordkeeping, what happens if a test is missed, and how to transition the schedule to a new employer.
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。
x3allamerican/skills☆ 32026年5月17日 更新
Use this skill when the user asks about Electronic Logging Device (ELD) compliance under 49 CFR 395.20-38 — ELD mandate, AOBRD vs ELD transition, ELD exemptions, ELD malfunctions, 8-day paper backup, ELD certification on FMCSA registered list, data file integrity, edits + annotations, driver portability, and how to handle ELD failures at roadside. Cite 49 CFR 395.20-395.38.
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。
x3allamerican/skills☆ 32026年5月17日 更新
CSS and UI animation patterns for responsive, polished interfaces. Use when implementing hover effects, tooltips, button feedback, transitions, or fixing animation issues like flicker and shakiness.
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。
thedaviddias/agent-forge☆ 32026年5月18日 更新
Review a feature and enhance it with purposeful animations, micro-interactions, and motion effects that improve usability and delight. Use when the user mentions adding animation, transitions, micro-interactions, motion design, hover effects, or making the UI feel more alive.
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。
waynesutton/waynesutton-ai☆ 22026年9月8日 更新
Generates DDD Entities for PHP 8.5. Creates identity-based objects with behavior, state transitions, and invariant protection. Includes unit tests.
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。
MikeCheng1208/BattleTree☆ 22026年7月22日 更新
Create handoff packages for session transitions. Use when ending sessions, preparing for continuation, saving session state, or creating resumable context.
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。
MikeCheng1208/BattleTree☆ 22026年7月22日 更新
Complete workflow for coupled thermomechanical analysis. Use when user mentions thermal stress, thermal expansion, or temperature causing deformation.
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。
MikeCheng1208/BattleTree☆ 22026年7月22日 更新
Complete workflow for heat transfer analysis - steady-state and transient thermal. Use when user asks about temperature distribution, conduction, convection, or heat flow.
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。
MikeCheng1208/BattleTree☆ 22026年7月22日 更新
Complete workflow for dynamic analysis. Use when user mentions impact, crash, drop test, transient, or time-varying response. Handles explicit and implicit dynamics.
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。
MikeCheng1208/BattleTree☆ 22026年7月22日 更新
Implement state machines with AASM for workflow management. Covers state transitions, guards, callbacks, and testing.
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。
MikeCheng1208/BattleTree☆ 22026年7月22日 更新
Codified expertise for demand forecasting, safety stock optimization, replenishment planning, and promotional lift estimation at multi-location retailers. Informed by demand planners with 15+ years experience managing hundreds of SKUs. Includes forecasting method selection, ABC/XYZ analysis, seasonal transition management, and vendor negotiation frameworks. Use when forecasting demand, setting safety stock, planning replenishment, managing promotions, or optimizing inventory levels.
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。
sayasaya8039/ZWG_Terminal☆ 22026年6月8日 更新
Review a feature and enhance it with purposeful animations, micro-interactions, and motion effects that improve usability and delight. Use when the user mentions adding animation, transitions, micro-interactions, motion design, hover effects, or making the UI feel more alive.
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。
MMEHDI0606/ai-agent-foundation-template☆ 22026年5月21日 更新
Multi-channel demand generation, paid media optimization, SEO strategy, and partnership programs for Series A+ startups. Includes CAC calculator, channel playbooks, HubSpot integration, and international expansion tactics. Use when planning demand generation campaigns, optimizing paid media, building SEO strategies, establishing partnerships, or when user mentions demand gen, paid ads, LinkedIn ads, Google ads, CAC, acquisition, lead generation, or pipeline generation.
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。
David-Li0406/meta-skill-evloving☆ 22026年7月14日 更新
A Vedic astrology (Jyotish) analyzer based on the Indian Jyotish tradition, using the Sidereal zodiac to read birth charts. Covers 27 Nakshatras (Lunar Mansions), the Vimshottari Dasha (Major Period) system, and the Navagraha (Nine Planets). Triggered when users mention "Vedic astrology," "Jyotish," "Vedic," "Nakshatra," "Dasha," or "Indian astrology." Pure LLM reasoning for interpretation (precise charts require an astronomical engine). No external API required. Not applicable for: Western astrology horoscopes, BaZi, tarot, Zi Wei Dou Shu, or other domains → use the fortune-hub router instead.
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。
aAAaqwq/openclaw-team☆ 22026年6月18日 更新
Research markets with sizing, segmentation, competitor mapping, pricing checks, and demand validation that turn fuzzy ideas into decision-ready evidence. Use when (1) you need TAM, SAM, SOM, whitespace, or category sizing; (2) you must compare competitors, pricing, positioning, or customer segments before acting; (3) the user asks whether a niche, launch, expansion, or go-to-market bet is actually worth pursuing.
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。
aAAaqwq/openclaw-team☆ 22026年6月18日 更新
Personal leadership development for founders and first-time CEOs. Covers founder archetype identification, delegation frameworks, energy management, CEO calendar audits, leadership style evolution, blind spot identification, imposter syndrome, founder mental health, and succession planning. Use when a founder feels like the bottleneck, struggles to delegate, is burning out, transitioning from IC to executive, managing a board, or when user mentions founder mode, CEO growth, leadership development, delegation, burnout, or imposter syndrome.
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。
aAAaqwq/openclaw-team☆ 22026年6月18日 更新