「topology」の検索結果

Generates Mermaid and ASCII diagrams of palace structure, knowledge topology, and synapse connectivity. Use when inspecting or presenting a palace visually.

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Use the city2graph 1.0.0 Python package to construct, validate, transform, and troubleshoot geospatial, spatial-topology, morphology, mobility, transportation, heterogeneous, and GNN-ready graphs.

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Review repository architecture using Ontoly Software Graph and MCP capabilities. Use when asked to explain architecture, module boundaries, package topology, service ownership, or architectural risk.

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Blender sculpting for organic and hard surface detail using Dyntopo, multiresolution, brushes, alpha workflow, wrinkles, and damage. Use when high-frequency surface detail is needed before retopology in Blender via MCP.

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Validates and optimizes Blender assets for polycount, topology, UV efficiency, material count, naming, collections, and game-ready performance. Use before export on all production assets via MCP.

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AAA character modeling for human anatomy, stylization, facial topology, clothing, hair, and animation-ready meshes. Use for game characters, facial expressions, and production character assets in Blender via MCP.

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Publication-figure overlay for draw.io. Use instead of drawio whenever the diagram is for a paper, thesis, dissertation, journal, conference, IEEE/ACM submission, manuscript, camera-ready, Word/LaTeX figure, or other publication. Applies venue, figure-type, color, caption/legend, formula, and paper-readability gates for architecture, workflow, roadmap, network-topology, and replicated paper figures.

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Create, edit, replicate, import, and export draw.io diagrams with an offline YAML-first workflow: architecture, network topologies, flowcharts, UML/ER, org charts, Mermaid/CSV conversion, existing .drawio bundles, style presets, themes, and non-publication formula diagrams. For publication figures (paper, thesis, IEEE, camera-ready) use drawio-academic-skills instead.

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Analyzes an existing codebase using strategic Domain-Driven Design to discover bounded contexts, surface ubiquitous language and semantic collisions, find places where code boundaries diverge from domain boundaries, and produce an evidence-backed domain and context map. Use when the goal is DDD-specific: bounded context discovery, ubiquitous language analysis, domain model discovery, or mapping contested ownership and responsibility. The entire repository is a valid scope; no module or directory must be named first. Does not assess architectural coupling, cohesion, or technical debt — use architectural-analysis. Does not design service communication, integration patterns, or deployment topology — use architectural-analysis or plan-a-feature. Does not refactor code, diagnose bugs, or review code quality — use refactor, investigate, or code-review.

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Audit Blender scenes and assets for topology, transforms, normals, surface continuity, classified connections, intersections, modifier/node intent, procedural performance, simulation stability, protected-scene changes, and fixed-view visual evidence. Use after every major modeling or simulation stage and before render, bake, export, or claims of completion.

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Orchestrate production-grade Blender work by probing the installed Blender version, retrieving relevant official Blender documentation, assigning visual design intent, classifying shape grammar and geometry/deformation/procedural/physics/shading needs, comparing direct Blender components with node systems, creating staged artifacts, and routing to specialist skills. Use for every non-trivial Blender creation, reconstruction, simulation, animation, environment, or scene-modification request, especially when the user does not know whether to use topology, Boolean, Array, curves, snapping, Displace, simulation, Geometry Nodes, or shading.

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Analyze a software repository at the latest remote main commit and turn its implemented architecture into a citation-backed interactive isometric system map with a legend, selectable infrastructure buildings, dependency and payload flows, and plain-language learner explanations. For eligible public GitHub repositories, also contribute the verified map to tamdogood/CodeTerrain with a pull request. Use when a user provides a repository URL or asks to visualize, explore, learn, explain, or map a repo's architecture, infrastructure, runtime control flow, data flow, services, queues, stores, external systems, or deployment topology in an interactive UI.

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Think and work like an expert Mathematical Analyst. Use when a task calls for Mathematical Analyst judgment. Reasons from function-space topology, convergence modes, and constant-dependent inequalities (Hölder, Sobolev, Gronwall) through compactness theorems (Rellich-Kondrachov, Banach-Alaoglu), Calderon-Zygmund and Schauder estimates, and Lax-Milgram while treating limit-integral swaps without dominated convergence, boundary-degenerating constants, weak-versus-classical regularity gaps, and concentration-compactness loss as first-class failure modes.

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Think and work like an expert Heliophysicist. Use when a task calls for Heliophysicist judgment. Reasons from MHD, magnetic topology, reconnection, and IMF Bz coupling through SDO/HMI magnetograms, DEM and NLFFF analysis, coronagraph GCS fitting, and WSA-ENLIL/EUHFORIA ensembles while treating LOS foreshortening, AIA stray light, force-free NLFFF breakdown, and Dst/SYM-H saturation as first-class failure modes.

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Think and work like an expert High-Performance Computing Specialist. Use when a task calls for High-Performance Computing Specialist judgment. Reasons from NUMA topology and hybrid MPI+OpenMP+CUDA decomposition through Slurm fairshare/backfill job design, strong/weak scaling (Amdahl/Gustafson), Darshan/mpiP/Nsight profiling, and parallel HDF5/MPI-IO on Lustre while treating I/O storms, collectives bottlenecks, and rank-binding mistakes as first-class failure modes.

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Think and work like an expert Epigeneticist. Use when a task calls for Epigeneticist judgment. Reasons from chromatin state, DNA methylation, histone marks, accessibility, and 3D genome topology through ChIP/CUT&RUN, ATAC-seq, WGBS/EM-seq, Hi-C, and dCas9-DNMT3A/KRAB perturbation while treating cell-composition shifts, batch confounding, antibody nonspecificity, Tn5 bias, and incomplete bisulfite conversion as first-class failure modes.

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Generate 3D assets with Tencent's Hunyuan3D family — open-weight self-hosted models (Hunyuan3D-2.0/2.1 and HunyuanWorld / HY-World for scenes) and the hosted, closed API tiers (2.5, PolyGen, 3.0/3.1 via Tencent Cloud and third-party hosts). Use when a task involves image-to-3D or text-to-3D mesh generation, the shape-then-texture (DiT + Paint / PBR) workflow, choosing between self-hosting and a hosted API, checking the Community License's Territory (EU/UK/South Korea) and 1M-MAU commercial gate, sizing GPU/VRAM for local inference, ComfyUI integration, or reviewing and post-processing (retopology, UVs, decimation) the meshes these models produce. Not for image, video, or general LLM tasks.

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Use this skill to turn generated, captured, scanned, or modeled 3D output into production-ready standalone assets for DCC, real-time engine, web, or interchange delivery. It covers requirements, topology repair, scale and axes, UVs, PBR baking, LODs, static and skeletal readiness, rig handoff, optimization, glTF/USD/FBX delivery, validation, QA, and rights/provenance. Do not use it for provider-specific generation prompts, full scene/world building, mocap operation, or exact CAD/manufacturing work.

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Create dark-themed, animated technical diagrams as self-contained HTML+SVG files — flowcharts whose connectors visibly flow, and architecture diagrams where requests travel as light dots through the system (Diagrid/Temporal landing-page style). Use this skill whenever the user asks for a flowchart, workflow, pipeline, process diagram, state machine, system architecture, infrastructure, cloud, microservices, or network topology diagram — and especially when they mention "animated", "flowing", "dynamic", "alive", "GIF-like", or want a diagram for a landing page, README, docs, or product demo. Also use it to convert Mermaid source (a mermaid code block or .mmd file) into an animated diagram — "animate this mermaid", "make this flowchart move". Prefer this over static diagram output whenever the diagram represents anything that moves: requests, events, data, jobs, messages, or control flow.

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Orchestrate multi-agent swarms with agentic-flow for parallel task execution, dynamic topology, and intelligent coordination. Use when scaling beyond single agents, implementing complex workflows, or building distributed AI systems.

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Orchestrate multi-agent swarms with agentic-flow for parallel task execution, dynamic topology, and intelligent coordination. Use when scaling beyond single agents, implementing complex workflows, or building distributed AI systems.

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Power system network data formats and topology. Use when parsing bus, generator, and branch data for power flow analysis.

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Deploy, manage, and debug Kubernetes in production — Deployments, Services, Gateway API, Service Mesh (Istio/Linkerd/Cilium), eBPF observability (Cilium Hubble), security hardening (Pod Security Standards, OPA/Kyverno, seccomp, runtime security with Falco/Tetragon), Helm, HPA, PDB, topology spread, and debugging. Use when user asks to write K8s manifests, deploy to a cluster, debug pods, set up Gateway API, configure autoscaling, or harden cluster security. Do NOT use for Dockerfiles (use docker), CI/CD pipeline design (use ci-cd), or Terraform infrastructure (use terraform).

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Designs cross-system target states and transition plans. Use when comparing end-to-end options or phased migrations. Not for in-service topology (software-architecture-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。