pydantic
無料Use when validating and serializing Python data with Pydantic v2 - models, field and model validators, constrained and special types, TypeAdapter, discriminated unions, BaseSettings, or FastAPI integration
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概要と使いどころ
Use when validating and serializing Python data with Pydantic v2 - models, field and model validators, constrained and special types, TypeAdapter, discriminated unions, BaseSettings, or FastAPI integration
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。
Zod schema validation patterns for TypeScript - schema definitions, type inference, refinements, transforms, discriminated unions
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Production-grade TypeScript reference for React & Next.js frontend development. Covers type narrowing, component Props, generic hooks, discriminated unions, as const, satisfies, Zod validation, TanStack Query, server/client boundaries, forms, state management, performance, accessibility, debugging, and code review. Use when the user works with TypeScript in React or Next.js: type errors, Props design, generics, API typing, SSR/CSR boundaries, hydration issues, form validation, state management, performance, or code review. Also use for "how should I type this?", "why does this type error happen?", or any architectural decision involving TypeScript in a frontend context.
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Build comprehensive chromatin accessibility maps by aggregating ATAC-seq and DNase-seq narrowPeak data across multiple ENCODE experiments, donors, and labs. Use when the user wants to answer "where is chromatin accessible in my tissue?" by combining peak calls into a union peak set. Handles cross-lab variation, ATAC vs DNase platform differences, and ENCODE blocklist filtering.
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。
Build comprehensive chromatin contact maps by aggregating Hi-C loop calls (BEDPE) across multiple ENCODE experiments, donors, and labs. Use when the user wants to answer "what regions are in 3D contact in my tissue?" by creating a union catalog of chromatin loops. Handles resolution-aware anchor matching, cross-lab variation, and Hi-C-specific quality metrics.
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。
Build comprehensive histone mark maps by aggregating narrowPeak data across multiple ENCODE experiments, donors, and labs. Use when the user wants to answer "where is this histone mark present in my tissue?" by combining peak calls from multiple studies into a union peak set with confidence annotations. Handles cross-lab batch effects, broad vs narrow marks, and ENCODE blocklist filtering.
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。
Implements advanced TypeScript type systems, creates custom type guards, utility types, and branded types, and configures tRPC for end-to-end type safety. Use when building TypeScript applications requiring advanced generics, conditional or mapped types, discriminated unions, monorepo setup, or full-stack type safety with tRPC.
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Audit film, television, and digital content production budgets for above-the-line (ATL) and below-the-line (BTL) cost accuracy, SAG-AFTRA/DGA/WGA/IATSE union rate compliance, fringe and payroll tax calculations, VFX bid variance analysis, post-production cost validation.
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Apply these opinionated TypeScript conventions whenever writing or reviewing TypeScript: branded types for domain modeling, discriminated unions for state, `satisfies` over `as`, const objects instead of enums, type-only imports, and the strict tsconfig baseline beyond `strict: true`. Also use for monorepo project references and incremental build setup.
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Auto-activate for msgspec, Struct, Meta, msgspec.json, msgspec.msgpack, tagged unions, enc_hook, dec_hook, convert(), or Litestar DTO shapes. Not for Pydantic or ORM models — use their stack-specific skill.
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Calls m6A peaks from MeRIP-seq / m6A-seq paired IP-vs-input data using exomePeak2 (transcript-aware, GC-bias-corrected Poisson GLM), MeTPeak (HMM over sliding windows), MACS3/MACS2 with --nomodel --broad --keep-dup all (genome-wide broad alternative), and DRACH motif enrichment via HOMER or ggseqlogo as a sanity check (NOT a filter). Covers BED12 vs narrowPeak output, exonic vs intronic peak handling, multi-tool reconciliation (intersection vs union), the m6A-vs-m6Am ambiguity at 5'UTR peaks that antibody methods cannot resolve, and orthogonal validation (miCLIP/GLORI/m6A-SAC-seq/m6Anet). Use when calling peaks from paired IP/input genome BAMs, choosing exomePeak2 (transcript-aware default) vs MACS3 (broad genomic) vs MeTPeak (HMM-smoothed low-coverage), confirming DRACH enrichment as a sanity check on the peak set, reconciling differing peak sets across tools, validating MeRIP peaks against single-base methods, interpreting 5' peaks where m6Am contamination is possible, or recommending a consensus strategy.
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-level data structures covering arrays, linked lists, trees, heaps, hash tables, graphs, and advanced structures like segment trees, tries, and union-find.
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Analyze WAF (ModSecurity/AWS WAF/Cloudflare) logs to detect SQL injection attack campaigns. Parses ModSecurity audit logs and JSON WAF event logs to identify SQLi patterns (UNION SELECT, OR 1=1, SLEEP(), BENCHMARK()), tracks attack sources, correlates multi-stage injection attempts, and generates incident reports with OWASP classification.
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Interactively build a Narrative identity graph workflow from one or more first-party datasets and (optionally) third-party data sources. Confirms each input dataset is mapped to the Rosetta Stone graph edge attribute (mapping it via /generate-rosetta-stone-mappings if not), then composes and submits a workflow that unions every edge source and labels connected components. Use when: "build an identity graph", "generate an identity graph", "create an identity graph", "stitch these datasets into a graph", "make a graph workflow", "label connected components on these datasets", "I want a person graph / household graph / device graph". (narrative-identity)
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Implements BLoC (v9.x) event-driven state management for Flutter with unidirectional data flow using the flutter_bloc package. Use when implementing Bloc/Cubit classes, mapping Events to States, consuming state with BlocBuilder/BlocListener/BlocConsumer, applying event transformers (restartable/droppable/sequential) for concurrency control, setting up BlocProvider/MultiBlocProvider DI, integrating Freezed for sealed union types and exhaustive pattern matching, or testing with blocTest. Ideal for enterprise apps requiring business logic separation, precise concurrency control (search debouncing, form deduplication), or event replay debugging.
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Reads an OpenAPI 3.0 specification and manually implements a type-safe Dart API layer using Dio for HTTP, Freezed or Equatable for models, and json_serializable for serialisation. Use when given an OpenAPI/Swagger file (JSON or YAML) and asked to implement the API in Flutter/Dart, create Dart models from an API schema, build a Dio API client, implement endpoints from a spec, convert openapi to dart, or set up a data/network layer from an API contract. Handles $ref resolution, oneOf union types, enums, query params, request bodies, and DioException error mapping.
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Converts TypeScript to idiomatic Dart 3 code, covering syntax mapping, type system translation, async patterns, and module migration. Activates when translating TypeScript interfaces, classes, enums, generics, union types, async/await patterns, or modules to Dart; migrating frontend or Node.js logic to Flutter/Dart; converting RxJS Observables to Dart Streams; adapting TypeScript utility types to Dart equivalents; or producing idiomatic Dart 3 output (sealed classes, records, pattern matching) from TypeScript source.
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Build and publish a Gradio demo on Hugging Face Spaces for a user-provided LoRA. Use when someone asks to create, generate, ship, or publish a Space, demo, Gradio app, or playground for a LoRA — including LoRAs for Qwen-Image, Qwen-Image-Edit, LTX-Video, Wan, FLUX, SDXL, or other diffusion base models. Also triggers when someone describes a LoRA they trained or hosts on the Hub and wants to share it. Covers picking the right base pipeline and `diffusers` inference recipe, designing a UI tailored to the LoRA's task and inputs (Union/multi-task control, edit, video, image, etc.), respecting model-card recommendations (trigger words, steps, guidance, LoRA scale, example inputs), and shipping to ZeroGPU hardware as a private Space by default.
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Liquid Glass material best practices for SwiftUI, UIKit, and AppKit on iOS 26+/macOS 26+ (Tahoe) through iOS 27/macOS 27. Use when implementing, reviewing, or migrating to glass: glassEffect, Glass variants (.regular/.clear/.identity), tint, interactive(), GlassEffectContainer, glassEffectUnion, toolbar glass, ToolbarSpacer, scrollEdgeEffectStyle, sharedBackgroundVisibility, tabBarMinimizeBehavior, backgroundExtensionEffect, NSGlassEffectView, UIGlassEffect, Tahoe window chrome, glass accessibility (Reduce Transparency/Increase Contrast), pre-26 Material fallbacks, UIDesignRequiresCompatibility. Also fires on symptoms: glass renders dark or muddy, glass looks like a flat tinted rectangle, glass button doesn't register taps, tap passes through glass, "'glassEffect' is only available in iOS 26.0 or newer", "ambiguous use of 'opacity'", "'cornerRadius' was deprecated", glass looks different in simulator vs device, screenshots of glass UI don't match. For glass animation, morphing, glassEffectID, transitions, Metal shaders, or performance profiling use the liquid-glass-motion skill 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。
Animation, morphing, and shader best practices for Liquid Glass and SwiftUI motion on iOS 26+/macOS 26+ through iOS 27. Use when animating glass or building UI motion: glassEffectID, @Namespace morphing, GlassEffectContainer spacing, glassEffectUnion, glassEffectTransition (.matchedGeometry/.materialize), withAnimation, springs, UnitCurve, PhaseAnimator, KeyframeAnimator, @Animatable, matchedTransitionSource, navigationTransition zoom, scrollTransition, visualEffect, Metal shaders (colorEffect, distortionEffect, layerEffect, [[stitchable]]), accessibilityReduceMotion gating, Instruments/xctrace profiling of hangs and animation hitches. Also fires on symptoms: glass morph not animating, view pops in instead of morphing, glass fades instead of materializing, morph flickers with Reduce Motion, menu glass morphs as a rectangle, animation runs on insert but not removal, PhaseAnimator loops forever or fires once, shader shows clipped edges (maxSampleOffset), animation hitches or main-thread hangs while scrolling glass chrome. For static glass, availability gating, toolbars, UIKit/AppKit glass, or accessibility of the material itself use the liquid-glass skill first.
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, review, or improve SwiftUI Liquid Glass effects for iOS 26+. Covers glassEffect modifier, GlassEffectContainer, glass button styles, glass toolbar, glass tab bar, morphing transitions, translucent material, vibrancy, tinting, interactive glass, ToolbarSpacer, scrollEdgeEffectStyle, backgroundExtensionEffect, and availability gating. Use when asked about Liquid Glass, glass buttons, glassEffect, GlassEffectContainer, GlassEffectTransition, glassEffectID, glassEffectUnion, scroll edge effects, or adopting iOS 26 design.
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 WAF (ModSecurity/AWS WAF/Cloudflare) logs to detect SQL injection attack campaigns. Parses ModSecurity audit logs and JSON WAF event logs to identify SQLi patterns (UNION SELECT, OR 1=1, SLEEP(), BENCHMARK()), tracks attack sources, correlates multi-stage injection attempts, and generates incident reports with OWASP classification.
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。
Detect primitive obsession and missing domain/brand types; check that state is modeled via discriminated unions.
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Generates, normalizes, and converts bedGraph signal tracks (4-column chrom/start/end/value, 0-based half-open) with bedtools genomecov, deepTools bamCoverage/bamCompare/bigwigCompare, bedtools unionbedg, and UCSC bedGraphToBigWig. Covers why a raw coverage bedGraph is not comparable across samples until normalized, the CPM/RPKM/BPM/RPGC normalization menu and the conserved-total assumption that makes them wrong under a global perturbation, the strict sorted-non-overlapping-chrom.sizes bedGraphToBigWig contract that silently corrupts a bigWig, effective-genome-size selection, and bin-size aliasing. Use when building or normalizing a coverage/signal track from a BAM, comparing tracks across samples or conditions, converting bedGraph to a browser-ready bigWig, or diagnosing a track that looks plausible but reports wrong heights.
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。