Use when creating or updating pull requests with comprehensive descriptions and meaningful commits - streamlines PR workflow with branch management and commit best practices
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。
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概要と使いどころ
Use when creating or updating pull requests with comprehensive descriptions and meaningful commits - streamlines PR workflow with branch management and commit best practices
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。
Capture solved problems as categorized documentation with YAML frontmatter for fast lookup
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。
Constraint-based metabolic modeling (COBRA). FBA, FVA, gene knockouts, flux sampling, SBML models, for systems biology and metabolic engineering analysis.
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 should be used when the user asks to "create a slash command", "add a command", "write a custom command", "define command arguments", "use command frontmatter", "organize commands", "create command with file references", "interactive command", "use AskUserQuestion in command", or needs guidance on slash command structure, YAML frontmatter fields, dynamic arguments, bash execution in commands, user interaction patterns, or command development best practices for Claude Code.
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。
制作、修改和验收中文手绘知识讲解视频,交付配音、字幕、时间轴、可编辑工程和真实 MP4。支持两条不可混淆的制作路线:同一画布持续落墨的逐笔故事动画,以及用 SVG/HTML/GSAP 编排流程卡片、关系图和知识图形的程序动画。逐笔路线可选择自然肤色 Q 版人物、小黑风格或其他手绘风格,并可采用单场景、多幕故事、左右双语义岛等画面结构。用户说“边讲边画”“一笔一笔画出来”“白板手绘”“先画左边再画右边”“知识讲解动画”或希望把文稿、SRT、人物故事做成手绘视频时使用。也支持只输出生图/图生视频提示词。不用于写实数字人或假装已经完成无法验证的成片。
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。
Create distinctive, production-grade frontend interfaces with high design quality. Use this skill when the user asks to build web components, pages, artifacts, posters, or applications (examples include websites, landing pages, dashboards, React components, HTML/CSS layouts, or when styling/beautifying any web UI). Generates creative, polished code and UI design that avoids generic AI aesthetics.
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。
Toolkit for styling artifacts with a theme. These artifacts can be slides, docs, reportings, HTML landing pages, etc. There are 10 pre-set themes with colors/fonts that you can apply to any artifact that has been creating, or can generate a new theme on-the-fly.
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 when escalating privileges on a Windows host — SeImpersonate Potato chains (GodPotato/PrintNotifyPotato), service & DLL hijacking, UAC bypass (fodhelper/ICMLuaUtil), kernel EoP + BYOVD (CVE-2025-29824), token-rights abuse, LSASS/SAM/DPAPI credential harvesting
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 when gaining initial access to a target — phishing, payload delivery, HTML smuggling, ISO/IMG/MOTW bypass, supply-chain, credential stuffing, exposed-service exploitation
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。
Diagrams and checkable docs from a codebase. Draws ERDs, C4 context/container/component views, API endpoint catalogues, lifecycle/state machines, sequence diagrams, and service-to-service call maps as a validated JSON spec plus a standalone HTML viewer, with Mermaid export. Imports OpenAPI, GraphQL SDL and Prisma; otherwise reads the code (NestJS, TypeORM, Express) and writes the spec. Use for: database diagram, ERD, data model, table relationships, C4 or architecture diagram, system context, API map, endpoint list, "show me the endpoints", status flow, state machine, allowed transitions, "what happens after X is approved", sequence diagram, request flow, how services call each other, microservice map, Mermaid diagram. Also writes documentation as a fact graph: each statement carries its source and a computed confidence, and a drift check fails CI when the code moves. Use to document a system, write architecture or onboarding docs, or explain how a system works.
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。
Create new Claude Code Skills with proper YAML frontmatter, progressive disclosure structure, and complete directory organization. Use when you need to build custom skills for specific workflows, generate skill templates, or understand the Claude Skills specification.
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。
Generate an interactive PR review walkthrough as an HTML page. Fetches PR data via gh API, categorizes files into core vs mechanical changes, adds reviewer annotations, and renders diffs with moved-code detection. Use when the user pastes a GitHub PR URL and asks for a review, walkthrough, or summary, or says "review this PR".
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 when adding cross-cutting concerns to durable functions — structured logging or tracing across all functions, error tracking with Sentry, payload encryption for sensitive data, dependency injection of clients (DB, Stripe, etc.) into function handlers, custom telemetry, or behavior that should apply uniformly across many functions. Covers Inngest middleware lifecycle, creating custom middleware, dependencyInjectionMiddleware, @inngest/middleware-encryption, @inngest/middleware-sentry, and custom middleware 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。
Scan a codebase for deepening opportunities, present them as a visual HTML report, then grill through whichever one you pick.
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。
Generate a self-contained HTML slide deck from a topic, outline, report, or data. Use for presentations and slide decks; not for editing PowerPoint files.
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。
Create an HTML color palette from a mood, description, or image, with swatches, color codes, pairings, and contrast checks. Use for color schemes or brand colors.
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。
GATK Best Practices for germline SNP/indel calling from WGS/WES BAMs. Per-sample HaplotypeCaller GVCFs, GenomicsDBImport, GenotypeGVCFs joint calling, VQSR or hard filters. Requires BWA-MEM2-aligned, markdup, BQSR BAMs. Use DeepVariant for a faster DL alternative; GATK is the NIH/ENCODE standard.
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。
Query the ClinPGx (formerly PharmGKB) REST API plus the CPIC PostgREST companion API for pharmacogenomic clinical annotations, CPIC/DPWG dosing guidelines, gene-drug pairs, variant-drug associations, FDA/EMA drug labels, and PGx pathways. Two-host architecture: api.clinpgx.org for annotation records, api.cpicpgx.org for genotype→recommendation lookups. No auth. For germline pathogenicity use clinvar-database; for somatic cancer PGx use cosmic-database or opentargets-database; for drug bioactivity use chembl-database-bioactivity.
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。
ENA REST API for sequences, reads, assemblies, and annotations. Portal API search, Browser API retrieval (XML/FASTA/EMBL), file reports for FASTQ/BAM URLs, taxonomy, cross-refs. For multi-DB Python use bioservices; for NCBI-only use pubmed-database or Biopython Entrez.
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。
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.
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。
Query ARCHS4 REST API for uniformly processed RNA-seq expression, tissue patterns, co-expression across 1M+ human/mouse samples. Retrieve z-scores, co-expressed genes, samples by metadata, HDF5 matrices. For variant population genetics use gnomad-database; for pathway enrichment use gget-genomic-databases (Enrichr).
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。
Aggregates QC from 150+ bioinformatics tools into one interactive HTML report. Scans FastQC, samtools, STAR, HISAT2, Trim Galore, featureCounts, Kallisto, Salmon, Picard, GATK logs; merges per-sample stats with plots. For NGS pipeline-wide QC. Use FastQC directly for single-sample; MultiQC for multi-sample reporting.
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。
Query COSMIC for cancer somatic mutations, gene census, mutational signatures, drug resistance variants. REST API v3.1 supports gene/sample/variant queries; free registration. For germline use clinvar-database; for drug-target data use opentargets-database or chembl-database-bioactivity.
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。
Rust-backed Python library for fast genomic token arithmetic and BED processing. High-performance BED I/O, interval set ops (intersect, merge, complement, subtract), region tokenization against a universe, universe construction. Use for preprocessing large BED collections and ML token vocabularies.
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。