1.4万 件 ・ 関連度順
概要と使いどころ
Guide users through browser automation setup using Chrome DevTools MCP only. Use when the user asks to set up browser automation, Chrome DevTools MCP, browser MCP, or runs the browser-setup command.
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。
Implement test-driven development (TDD) workflow using the red-green-refactor cycle. Use when writing new features, fixing bugs, or refactoring existing code. Always write the failing test first, then implement minimal code to pass, then refactor. Essential for ensuring code reliability, preventing regressions, improving design through testability requirements, documenting expected behavior through tests, enabling confident refactoring, and maintaining high code quality standards throughout the development process.
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。
Orchestrate one or more thinking frameworks to work through any problem, decision, document, or idea rigorously. Diagnoses which frameworks fit — inversion, pre-mortem, assumption-mapping, socratic, adversarial-hat — then guides the user through them in the right sequence. Load when the user asks for deep thinking, says "help me think through this properly", "apply your best thinking frameworks", "I need to think carefully before deciding", or "what thinking tools should I use here". Also the entry point for any complex problem where the right framework is unclear. Covers product decisions, engineering tradeoffs, personal decisions, strategy, creative challenges — any domain.
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。
Loads, converts, and manipulates Hi-C contact matrices in cooler format (.cool/.mcool/.scool) and Juicer .hic, using cooler (Python + CLI), hic2cool, and hictk. Covers the single-resolution mcool URI (file.mcool::/resolutions/<bp>), the load-bearing divisive-vs-multiplicative weight-naming rule (KR/VC/VC_SQRT auto-divisive vs cooler's multiplicative weight), what survives .hic<->.cool conversion (FRAG matrices and norm vectors do not), raw-vs-balanced coarsening, the .pairs upper-triangle/chromsize-order contract, and chrom-naming/bin-table provenance. Use when loading a cooler, converting .hic to .mcool, selecting a resolution, building a cooler from pairs or a matrix, coarsening/zoomifying, importing Juicer norm vectors, or debugging all-NaN balanced matrices and chr1-vs-1 empty fetches.
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。
Orders and orients assembled contigs into chromosome-scale scaffolds from long-range linking data, inserting N-gap spacers (adds no sequence). Covers Hi-C/Omni-C scaffolding (YaHS, SALSA2, 3D-DNA/Juicer), Hi-C read-mapping prerequisites (map each end separately, no mate rescue, dedup, enzyme-aware), reading the contact map for misjoins/inversions/false-duplications, manual curation in Juicebox/PretextView (the VGP/DToL standard), reference-guided scaffolding (RagTag) and its karyotype-erasure hazard, genetic-map (ALLMAPS) and Bionano optical-map integration, chimera-breaking before scaffolding, gap-filling, and telomere/contig-vs-scaffold-N50 QC (tidk). Use when turning contigs into chromosomes with Hi-C, integrating a linkage map or optical map, choosing a scaffolder by available linking data, or judging whether a chromosome-scale assembly is trustworthy.
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。
Handles BED-format genomic intervals (BED3 through BED12, narrowPeak/broadPeak) and the coordinate-system substrate the whole interval category rests on, with bedtools (CLI) and pybedtools/pyranges/pandas (Python). Covers the 0-based half-open vs 1-based-closed convention boundary and the start-1/end-unchanged conversion, the silent failures (chrom-name mismatch, CRLF, lexicographic-vs-version sort under -sorted), genome/chrom.sizes generation, sorting contracts, BED12 block invariants, validation, makewindows, cross-assembly liftover (liftOver/CrossMap), and BED<->VCF/BAM/FASTA conversion. Use when reading, creating, validating, sorting, lifting between genome builds, or converting interval files, preparing inputs for bedtools/tabix/bigBed, or debugging an off-by-one or empty-overlap result.
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。
Performs differential expression on bulk RNA-seq count data with DESeq2's negative-binomial GLM, Wald and LRT testing, apeglm/ashr/normal LFC shrinkage, independent filtering, Cook's outlier handling, VST/rlog transforms, and design formulas including paired, batch, and interaction terms. Use when running bulk DE, choosing DESeq2 over edgeR or limma-voom, building a paired or interaction design, applying LFC shrinkage for ranking or GSEA, choosing Wald vs LRT, troubleshooting padj=NA, picking VST vs rlog, importing salmon/kallisto via tximport, or analyzing prokaryotic RNA-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。
Infers person-to-person transmission from pathogen genomes using outbreaker2 (Campbell 2018), TransPhylo (Didelot 2017), phybreak (Klinkenberg 2017), BadTrIP (De Maio 2018), SCOTTI (De Maio 2016), BEASTLIER (Hall 2015), and SNP-distance / cluster-picker approaches (HIV-TRACE for HIV; transcluster). Defines outbreak clusters using pathogen-specific SNP thresholds (NOT a universal cutoff -- TB <=12 SNPs / Walker 2013; MRSA <=15 / Coll 2017; C. difficile <=2 / Eyre 2013; Klebsiella <=21 / Snitkin 2012), models within-host diversity and transmission bottlenecks (Worby-Lipsitch-Hanage 2014; McCrone 2018; Sobel Leonard 2017; Lythgoe 2021 SARS-CoV-2), integrates contact-tracing data, distinguishes generation interval from serial interval (Britton & Scalia Tomba 2019; Ali 2020), attributes source via Bayesian source attribution (Mather 2013 DT104; islandR), and reconciles transmission-network reconstruction with epi metadata. Use when investigating outbreaks for who-infected-whom, defining SNP-cluster outbreak definitions, accounting for unsampled intermediates, choosing between outbreaker2 (rich epi data) and TransPhylo (genomic-only after dated phylogeny), running source attribution between host populations, calling HIV-TRACE thresholds appropriate to the local subtype, or distinguishing recent transmission from reactivation in TB / chronic HIV.
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。
Identify differentially accessible chromatin regions across conditions using DiffBind, csaw, DESeq2, or edgeR. Use when comparing ATAC-seq accessibility between treatment groups, choosing between consensus-peak vs sliding-window approaches, picking the correct normalization (full library vs reads-in-peaks), correcting batch with SVA/RUVseq, or interpreting log2FC and FDR thresholds in a chromatin 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。
Process and analyze single-cell ATAC-seq data with Signac, ArchR, SnapATAC2, or Cell Ranger ATAC. Use when handling 10X scATAC or 10X Multiome (paired RNA+ATAC) data, performing per-cell QC, choosing between ArchR/Signac/SnapATAC2 ecosystems, building per-cluster consensus peaksets, integrating with paired scRNA-seq, doublet detection (AMULET vs ArchR vs scDblFinder), or running pseudobulk differential accessibility per cluster.
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。
Design desktop window systems that feel native on macOS and Windows: split views, inspectors, auxiliary windows, tiling, snap-safe sizes, default placement, and chrome density. Use when a Tauri/Electron/WinUI/SwiftUI app feels awkward, overlapping, over-chromed, or generic, or when you need a real geometry contract for multiple surfaces. NOT for mobile layouts, marketing pages, or CSS-only component styling without multi-window or multi-pane behavior.
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。
Token bucket, sliding window, and Redis-based rate limiting for API protection. Activate on: rate limiting, throttling, token bucket, sliding window, API abuse, DDoS protection, quota management. NOT for: API gateway setup (use api-gateway-reverse-proxy-expert), caching (use cache-strategy-invalidation-expert).
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。
Ahrefs API analyst (extension). Reads referring domains, backlinks, organic keywords, and content explorer data via the tested @ahrefs/mcp@0.0.11 server. Pairs with seo-backlinks for multi-source confidence weighting.
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Builds simple Three.js web apps with scene setup, lighting, geometry, materials, animation, and responsive rendering. Use when creating or prototyping 3D web scenes with modern Three.js (r150+).
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。
Analyze an idea, proposal, change, claim, or decision from facts through problem, value, mechanism, consequences, evidence, alternatives, and action. Use when the user asks what something is for, why it matters, whether it is worth doing, what impact it has, or how to decide. Do not use for simple factual lookup or straightforward execution.
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。
Expert in Three.js, 3D graphics, and interactive 3D visualizations
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。
3D web graphics with Three.js (WebGL/WebGPU). Capabilities: scenes, cameras, geometries, materials, lights, animations, model loading (GLTF/FBX), PBR materials, shadows, post-processing (bloom, SSAO, SSR), custom shaders, instancing, LOD, physics, VR/XR. Actions: create, build, animate, render 3D scenes/models. Keywords: Three.js, WebGL, WebGPU, 3D graphics, scene, camera, geometry, material, light, animation, GLTF, FBX, OrbitControls, PBR, shadow mapping, post-processing, bloom, SSAO, shader, instancing, LOD, WebXR, VR, AR, product configurator, data visualization, architectural walkthrough, interactive 3D, canvas. Use when: creating 3D visualizations, building WebGL/WebGPU apps, loading 3D models, adding animations, implementing VR/XR, creating interactive graphics, building product configurators.
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。
Complete color manipulation and green screen effects system. PROACTIVELY activate for: (1) Green screen/chromakey removal, (2) Color grading with LUTs, (3) Color correction (levels, curves, white balance), (4) Colorkey/color removal effects, (5) Hue/saturation manipulation, (6) Color space conversions (BT.709, BT.2020, HDR), (7) Color isolation effects, (8) Teal and orange look, (9) Vintage/film looks, (10) Color keying for transparency. Provides: chromakey and colorkey filters, LUT application (lut3d), curves and levels adjustment, color balance, selective color manipulation, color space handling, HDR tone mapping, professional color grading chains.
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。
Decision validation and thinking frameworks for startup founders. Use when you need to pressure-test a decision, validate your next steps, think through strategic options, or sanity-check your approach. Triggers on phrases like "should I", "help me think through", "is this the right move", "validate my thinking", "what am I missing". Covers fundraising, customer development, runway management, prioritization, and crypto/web3 founder challenges.
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。
Security review and threat work — threat modeling, vulnerability assessment, penetration test, incident response, OWASP Top 10, LLM Top 10, API Top 10, CVE triage, STRIDE, NIST CSF, SBOM. Auto-loops on any task touching PII, auth, payments or regulated data.
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。
Use this skill to create CodeTour .tour files — persona-targeted, step-by-step walkthroughs that link to real files and line numbers. Trigger for: "create a tour", "make a code tour", "generate a tour", "onboarding tour", "tour for this PR", "tour for this bug", "RCA tour", "architecture tour", "explain how X works", "vibe check", "PR review tour", "contributor guide", "help someone ramp up", or any request for a structured walkthrough through code. Supports 20 developer personas (new joiner, bug fixer, architect, PR reviewer, vibecoder, security reviewer, and more), all CodeTour step types (file/line, selection, pattern, uri, commands, view), and tour-level fields (ref, isPrimary, nextTour). Works with any repository in any language.
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。
Test naming conventions and best practices specialized skill. Used when naming test methods, improving test readability, and establishing naming standards. Covers three-part naming method, Chinese naming recommendations, test class naming, etc. Keywords: test naming, test naming, naming conventions, naming conventions, three-part naming, three-part naming, method_scenario_expected, method_scenario_expected, how to name tests, test readability, naming best practices, test report, test documentation
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。
Implement User and Entity Behavior Analytics using Elasticsearch/OpenSearch to build behavioral baselines, calculate anomaly scores, perform peer group analysis, and detect insider threat indicators such as data exfiltration, privilege abuse, and unauthorized access patterns.
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。
This skill teaches security teams how to deploy and operationalize Amazon GuardDuty for continuous threat detection across AWS accounts and workloads. It covers enabling protection plans for S3, EKS, EC2 runtime monitoring, and Lambda, interpreting finding severity levels, and building automated response workflows using EventBridge and Lambda.
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。