1.1万 件 ・ 関連度順
概要と使いどころ
Best practices for AI-driven English-to-Chinese translation. This skill should be used when the user asks to "translate to Chinese", "update the Chinese translation", "improve Chinese translation", "fix translation quality", "review Chinese translation", or when translating any English text into Chinese. Also applies when polishing an existing Chinese translation of English content.
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。
Execute ENCODE ChIP-seq processing pipeline from FASTQ to peaks and signal tracks. Child of pipeline-guide. Provides stage-by-stage Nextflow execution with Docker containers and cloud deployment. Use when users need to process ChIP-seq data following ENCODE standards, run peak calling with MACS2, perform IDR analysis, or generate signal tracks. Trigger on: ChIP-seq pipeline, run ChIP-seq, process ChIP-seq, MACS2 peak calling, IDR analysis, ChIP-seq FASTQ processing.
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。
Archive multiple completed OpenSpec changes at once. Use when archiving several parallel changes. Also use for a plural archive request - "openspec bulk-archive", "opsx bulk-archive", "openspec archive all", or "openspec archive these changes".
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。
Run work as an explicit event-driven state machine executed by subagents. The orchestrator is the runtime from the canonical loop — `state, effects = init(machine); execute(effects); while state is active: event = nextEvent(); state, effects = transition(machine, state, event); execute(effects); return state.output`. All routing judgment is authored ONCE, at plan time, into a machine file (states, event alphabet, transition table, budgets, final states); at runtime the orchestrator does pure table lookups and dispatches effects — it never decides, never authors, never ingests artifacts. Subagent/sync protocol is the timeboxed-iterating one: role prompts scaffolded once to disk and dispatched BY PATH, an initialiser preamble every subagent reads first, a self-populating cheatsheet, per-unit files, tiny structured returns, independent measurement gate. Use when the user says "workmachine", "run this as a state machine", "state-machine this", or when a goal has a small number of clearly named phases with explicit outcomes (built / passed / failed / blocked) and you want the routing to be auditable rather than judged on the fly. For clock-driven loops use timeboxed-iterating; for wide graphs with judged edge criteria use workgraph.
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 the architecture guidelines for a game project. Scans the project structure and tech stack, then produces .unikit/ARCHITECTURE.md describing the folder layout, dependency rules, and how modules communicate. Name a specific pattern or let it auto-detect. Use when the user wants to define or document the project architecture, e.g. "generate architecture", "describe the architecture", "which architecture should I use", "set up project architecture", or mentions module structure, module boundaries, project organization, or dependency rules.
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。
Application architecture patterns and code organization — clean architecture, hexagonal architecture, feature-based structure, dependency inversion, module boundaries, SOLID principles at module scale. Activate on "clean architecture", "hexagonal architecture", "feature-based structure", "dependency inversion", "module boundaries", "architecture pattern", "folder structure", "fat controller", "circular dependency", "IoC container". NOT for microservice decomposition (use microservices-patterns) or database schema design (use database-design-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。
Application architecture patterns and code organization — clean architecture, hexagonal architecture, feature-based structure, dependency inversion, module boundaries, SOLID principles at module scale. Activate on "clean architecture", "hexagonal architecture", "feature-based structure", "dependency inversion", "module boundaries", "architecture pattern", "folder structure", "fat controller", "circular dependency", "IoC container". NOT for microservice decomposition (use microservices-patterns) or database schema design (use database-design-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。
NanoClawの対話環境で、Markdownに保存したセッションの再開・分岐・横断検索・履歴圧縮・書き出しを扱い、モデル切り替えやスキル読み込みも支援します。
Generate architecture documentation using C4 model Mermaid diagrams. Use when asked to create architecture diagrams, document system architecture, visualize software structure, create C4 diagrams, or generate context/container/component/deployment diagrams. Triggers include "architecture diagram", "C4 diagram", "system context", "container diagram", "component diagram", "deployment diagram", "document architecture", "visualize architecture".
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 architecture documentation using C4 model Mermaid diagrams. Use when asked to create architecture diagrams, document system architecture, visualize software structure, create C4 diagrams, or generate context/container/component/deployment diagrams. Triggers include "architecture diagram", "C4 diagram", "system context", "container diagram", "component diagram", "deployment diagram", "document architecture", "visualize architecture".
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。
Guided journey from an app idea to a deliberate architecture: boundaries, domain model, data decisions, and resilience, making only the expensive-to-reverse decisions and deferring the rest. Orchestrates eight skills phase by phase - clean-architecture, domain-driven-design, system-design, ddia-systems, software-design-philosophy, release-it, pragmatic-programmer, 37signals-way - asking the user questions at every decision point and recording results in the project docs/ folder (ARCHITECTURE.md, DESIGN-CODE-ARCHITECTURE-PLAN.md) so the journey resumes across sessions. Use when the user wants to design a new app's architecture, choose boundaries and a domain model, decide monolith versus microservices, or says 'how should I structure this app'. If a codebase already exists, use remove-technical-debt (aged), improve-code-quality (fresh prototype), or architecture-optimization (slow but working); if unvalidated, run create-business or create-app first. For one framework in isolation, invoke that skill directly.
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 the user wants to inspect, list, extract, unpack, or repack Bethesda BA2/BSA archives; determine archive format/version/compression; or build archive assets for an MO2 overlay. Triggers - "unpack BA2", "extract BSA", "pack archive", "inspect archive", "bgs-archive".
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。
Trains and applies base-resolution deep learning models on ChIP-seq / ChIP-nexus / CUT&RUN data. Uses BPNet (Avsec 2021 Nat Genet 53:354; soft motif syntax from ChIP-nexus), chromBPNet (Pampari A et al 2024 bioRxiv; bias-factorized base-resolution profiles), EnFormer (Avsec 2021 Nat Methods 18:1196; 196 kb input, ~100 kb effective receptive field), DeepSEA (Zhou 2015; multi-task CNN), and JASPAR 2026 deep-learning collection (1259 BPNet ChIP models). Performs in silico mutagenesis for variant-effect prediction, DeepLIFT/Grad attribution, and TF-MoDISco motif discovery from attribution scores. Use when predicting variant effects on TF binding, discovering soft motif syntax / cooperativity, integrating ChIP-seq with sequence-only predictions, or applying precomputed JASPAR Deep Learning models to new variants.
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 China-specific financial skills following the established patterns and conventions. Use this meta-skill to scaffold new china-* skills that integrate with iFind MCP (Tier-1) and AkShare MCP (Tier-2 fallback), follow CAS accounting standards, and adapt workflows for the Chinese market. Triggers on "创建中国skill", "新建A股skill", "create china skill", "new china-skill", "制作skill", or when creating any new china-* skill.
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 knowledge for SQL Server on Azure Virtual Machines development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when planning SQL VM vs Managed Instance, Always On/FCI HADR, DTU/capacity limits, Key Vault/MI security, or Blob backups, and other SQL Server on Azure Virtual Machines related development tasks. Not for Azure SQL Database (use azure-sql-database), Azure SQL Managed Instance (use azure-sql-managed-instance), Azure Virtual Machines (use azure-virtual-machines), Azure Data Science Virtual Machines (use azure-data-science-vm).
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 knowledge for Azure Data Science Virtual Machines development including troubleshooting, decision making, architecture & design patterns, security, configuration, integrations & coding patterns, and deployment. Use when managing DSVM images/tools, IaC deployment (Bicep/ARM), Key Vault secrets, MLflow, or GPU/Jupyter issues, and other Azure Data Science Virtual Machines related development tasks. Not for Azure Virtual Machines (use azure-virtual-machines), Azure Machine Learning (use azure-machine-learning), Azure Databricks (use azure-databricks), Azure HDInsight (use azure-hdinsight).
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。
Quick-reference card for Chisle commands. One-shot display, not a persistent mode. Use when the user says "chisle help", "how do I use chisle", "what chisle commands", or invokes /chisle-help.
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。
Maximum-efficiency dev mode: terse zero-fluff prose + YAGNI/ladder-first code. Use when user says "chisle mode", "activate chisle", "chislify", "be efficient", "be minimal", "no fluff", "yagni", or invokes /chisle. Deactivate: "stop chisle" / "normal mode".
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。
Architecture patterns, design principles, and proven recipes for building robust robotics software. Use this skill when designing robot software architectures, choosing between behavioral frameworks, structuring perception-planning-control pipelines, implementing state machines, designing safety systems, or architecting multi-robot systems. Trigger whenever the user mentions behavior trees, finite state machines, subsumption architecture, sensor fusion, robot safety, watchdogs, heartbeats, graceful degradation, hardware abstraction layers, real-time constraints, or software architecture for robots. Also applies to sim-to-real transfer, digital twins, and robot fleet management.
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。
Fix JSON parse errors when fetching archived API responses from Wayback Machine. Use when: (1) Getting "Expecting value: line 1 column 1 (char 0)" JSON decode errors from archived URLs, (2) Wayback returns HTML instead of expected JSON/raw content, (3) Crawling archived REST APIs or JSON endpoints from web.archive.org. The `id_` modifier returns raw content without the Wayback toolbar wrapper.
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。
Trains and applies base-resolution deep learning models on ChIP-seq / ChIP-nexus / CUT&RUN data. Uses BPNet (Avsec 2021 Nat Genet 53:354; soft motif syntax from ChIP-nexus), chromBPNet (Pampari A et al 2025 Nat Genet; bias-factorized base-resolution profiles), EnFormer (Avsec 2021 Nat Methods 18:1196; 196 kb input, ~100 kb effective receptive field), DeepSEA (Zhou 2015; multi-task CNN), and JASPAR 2026 deep-learning collection (1259 BPNet ChIP models). Performs in silico mutagenesis for variant-effect prediction, DeepLIFT/Grad attribution, and TF-MoDISco motif discovery from attribution scores. Use when predicting variant effects on TF binding, discovering soft motif syntax / cooperativity, integrating ChIP-seq with sequence-only predictions, or applying precomputed JASPAR Deep Learning models to new variants.
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。
Define how system components connect, establishing boundaries, patterns, and integration approaches during PRD v0.6 Architecture. Triggers on requests to design architecture, create system design, define component relationships, or when user asks "design architecture", "system design", "how do components connect?", "architecture decisions", "technical architecture", "system overview". Consumes TECH- (stack selections), RISK- (constraints), FEA- (features). Outputs ARC- entries documenting architecture decisions with rationale. Feeds v0.6 Technical 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。
Architecture Patterns workflow skill. Use this skill when the user needs Master proven backend architecture patterns including Clean Architecture, Hexagonal Architecture, and Domain-Driven Design to build maintainable, testable, and scalable systems and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.
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。
architect-review workflow skill. Use this skill when the user needs Master software architect specializing in modern architecture and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.
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。