「its」の検索結果

Reverse-lookup glossary that turns a vague description of a web animation or motion effect into its exact term ("the bouncy thing when a popover opens" → Pop in; "the iOS rubber-band scroll" → Rubber-banding). Use when the user asks "what's it called when…", or describes a motion effect without knowing its name and wants the right word to prompt an AI or designer with. For naming an effect, not designing or building one.

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All-in-one FASTQ QC and adapter trimming. Auto-detects Illumina adapters, filters low-quality reads, corrects paired-end overlaps, emits HTML+JSON QC in one pass. 3-10x faster than Trim Galore/Trimmomatic. First step before STAR, BWA-MEM2, or Salmon.

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Retrieve mouse phenotype data from the Jackson Laboratory Mouse Phenome Database (MPD) via its REST API. Browse 520+ projects, look up per-project measure metadata, pull strain-level means (raw or LS-mean adjusted) and per-animal values, find measures by MP/VT ontology terms, and resolve strain nomenclature or gene coordinates. Use for QTL support, cross-strain comparison, mouse model selection, and ontology-driven phenotype discovery. Use monarch-database for disease-gene-phenotype knowledge graphs; ensembl-database for mouse genome annotations.

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NHGRI-EBI GWAS Catalog REST API for SNP-trait associations from published GWAS. Query studies, associations, variants, traits, genes, summary stats. Build PRS candidates, analyze pleiotropy, fetch stats for Manhattan plots. No auth.

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Therapeutics Data Commons (TDC) AI-ready drug discovery datasets. Curated ADME, toxicity, DTI, DDI with scaffold/cold splits, standardized metrics, molecular oracles, and ADMET benchmarks for therapeutic ML and property prediction. For chemical database queries use chembl-database-bioactivity; for featurization use molfeat.

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Medicinal chemistry filters for compound triage. Drug-likeness rules (Lipinski Ro5, Veber, Oprea, CNS, leadlike, REOS, Golden Triangle, Ro3), structural alerts (PAINS, NIBR, Lilly Demerits), chemical group detectors, complexity metrics, and filter composition query language. Built on RDKit/datamol. For hit-to-lead filtering, library design, ADMET pre-screening. For molecular I/O use rdkit-cheminformatics or datamol.

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Query the ZINC22 virtual compound library (CartBlanche API, billions of make-on-demand + purchasable molecules). Look up substances by ZINC ID, resolve a SMILES to its ZINC ID (exact match), inspect purchasability/catalogs, and assemble compound sets for docking. Property (MW/logP) filtering is done locally with RDKit. For bioactivity use chembl-database-bioactivity; for approved drugs use drugbank-database-access.

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Cancer Research (AACR) figures: resolution (300-1200 DPI), formats (EPS/TIFF/AI), hierarchical panel labels (Ai, Aii, Bi), figure/table limits, legend requirements with replicate counts.

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Symbolic math in Python: exact algebra, calculus (derivatives, integrals, limits), equation solving, symbolic matrices, ODEs, code gen (lambdify, C/Fortran). Use for exact symbolic results. For numerical use numpy/scipy; for stats use statsmodels.

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Assemble multiple plots into ONE publication-ready multi-panel journal figure (e.g. Figure 1 with panels A, B, C). Use whenever the user asks to combine, compose, or lay out several plots as a single composite figure — newly plotted from data or from already-rendered panels the user supplies (PNG/PDF). Ask the user to pick one of two approaches: (1) redraw every panel into one unified figure using independent, tightly packed `subfigures` (each sized to its own labels, so axes need NOT align), consistent style, correctly placed panel letters, and per-panel legends/colorbars; (2) composite already-rendered PNG/PDF panels onto a mosaic canvas and add panel letters (image compositing, not plotting). Both export vector PDF + high-DPI PNG. For a SINGLE plot from a data table, use the sibling `omics-plotting` skill instead.

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omics-plotting: publication-style figure authoring for omics / bioinformatics results with matplotlib / seaborn. Read this before writing any plotting or figure code in any omics analysis — RNA-seq, proteomics, single-cell, variant, or database results — not only when a plot is explicitly requested: whenever an analysis will produce a figure, load this first and follow its recipes. Covers volcano, MA, expression / correlation heatmap, GSEA bar / dot plot, box / violin / bar / ridgeline, PCA / UMAP / t-SNE scatter, Kaplan–Meier, Manhattan / QQ / forest. Supplies a shared journal-ready style and copy-paste recipes so every figure looks like one consistent system. To combine several plots into ONE multi-panel composite figure, use the sibling `multipanel` skill.

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Look up NYC DOB permits and new-building, alteration, or demolition job filings. Use for filed or permitted work and renovation history; use nyc-dob-violations for violations.

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Help users connect Arch Studio, understand its access and memory, choose a first workflow, and troubleshoot from reported evidence. General architecture and project execution stays with its owning skill.

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This skill should be used when the user asks about the invoice system (インボイス制度), qualified invoices (適格請求書), registration numbers (登録番号), input tax credits (仕入税額控除), the 20% special measure (2割特例), the 30% special measure (3割特例), tax-exempt businesses (免税事業者), transitional measures (経過措置), small-amount exceptions (少額特例), corrected invoices (修正インボイス), or any related topics. Trigger phrases include: "インボイス", "適格請求書", "登録番号", "仕入税額控除", "2割特例", "3割特例", "免税事業者", "経過措置", "少額特例", "修正インボイス", "返還インボイス", "簡易インボイス", "インボイス登録", "T番号", "適格請求書発行事業者".

This skill manages furusato nozei (hometown tax) donations. Use when the user wants to register donation data, read donation receipts, check deduction limits, or manage their furusato nozei records. Trigger phrases: "ふるさと納税", "furusato", "寄附金", "寄付金", "ふるさと納税の控除", "寄附金受領証明書", "ワンストップ特例".

Background context for housing loan tax credit (住宅ローン控除) in the shinkoku tax filing plugin. Contains eligibility requirements, credit limits, calculation rules, and interaction with furusato-nozei for the current tax year. This skill is not user-invocable — Claude loads it automatically when responding to housing loan tax credit questions or calculations.

コンテンツ戦略の立案、トピック選定、記事テーマ決めを行うスキル。 「コンテンツ戦略を立てて」「何を書けばいい？」「ブログのテーマを考えて」等のリクエストで発動。 For writing individual pieces, see copywriting. For SEO-specific audits, see seo-audit.

Builds and edits PowerPoint decks bound to a company's own .pptx or .potx template, with a consulting-grade storyline and a rendered visual QA pass. Maps the template's masters, layouts, placeholders, theme colors and fonts; drafts a storyboard of action titles (pyramid principle, SCR) for approval; fills the template's own placeholders instead of drawing text boxes; adds native charts in theme colors, tables sized to placeholders, speaker notes and source lines; then renders every slide to PNG and checks text overflow, off-slide and overlapping shapes, off-theme fonts and colors, empty placeholders and weak titles. Use whenever the user says use our template, company deck, brand or corporate template, make slides, build a deck, pptx, potx, consulting-style deck, board or client presentation, action titles, or fix my deck formatting, and whenever an existing deck must be edited without breaking its masters. Complements the generic pptx skill.

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Pulls financial statement numbers for US public companies straight from SEC EDGAR's free official XBRL APIs (companyfacts, companyconcept, frames, submissions) into a cited table. Every value carries its accession number, form, fiscal period, filed date, XBRL tag and a link to the filing, and the tool handles fiscal-year ends, quarterly vs YTD vs TTM, derived Q4, restatements and units. Use this whenever the user wants 10-K numbers or 10-Q numbers, says "pull financials for", asks for public company revenue, net income, EPS, cash, debt or capex, wants comps or a competitor side-by-side, a credit check, prospect research, or model inputs, or mentions SEC filings or EDGAR, even if they never say XBRL. Free and primary-source, no paid data terminal needed. Do not use it for private companies, stock prices or valuation multiples.

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Point Cowork at a folder of medical bills and insurance EOBs -- matches every bill to its explanation of benefits, catches duplicate charges, balance-billing, and bills that ignore your insurance, then drafts the dispute letters and phone scripts. Most medical bills contain errors; this finds them.

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Deploy a 2-layer parallel agent hierarchy for large, parallelizable work — big refactors, multi-file migrations, codebase-wide audits, bulk generation. A top-tier commander (Fable or Opus) orchestrates the swarms; the user picks a power level (Max Power / Heavy / Balanced / Economy) that sets the Opus/Sonnet/Haiku model mix per layer. Layer 1 is 3-50+ specialist agents, each with its own full context window; Layer 2 is 2+ sub-agents per member. Includes git safety, tiered sizing, a pre-deploy gate, phantom-completion checks, and multi-wave follow-up.

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Audits Rust code for unsafe blocks, ownership issues, and Cargo dependency risks. Use when reviewing Rust code or before merging Rust changes.

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Decompose a session into typed handoff units and recall them later. Use when ending a session or resuming work whose prior state must be recovered.

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Use when checking whether a manuscript's references are real. Audits each citation against PubMed and CrossRef, flags fabricated or mismatched entries and writes qc/reference_audit.json. Audit-only; never edits references or refs.bib. Citation-key checks are /manage-refs.

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。