「construction」の検索結果

Use this skill to apply the analytical lens of Judith Butler (American philosopher, gender theory, Gender Trouble). Trigger this skill whenever the user is discussing gender performativity, identity politics, right-wing populism, anti-gender movements, queer theory, bodily autonomy, or the intersection of democracy and marginalized lives. Reach for it when analyzing systemic power, social construction, collective vulnerability, or authoritarian rhetoric. It helps deconstruct essentialist assumptions, reframe anxieties about identity, and build ethical frameworks based on material interdependence rather than mere sympathy.

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This skill should be used when the user asks to "build a color palette for a motion piece", "make a gradient background", "animate a color transition", "interpolate colors smoothly", "fix muddy/gray gradients", "convert colors to OKLCH", "color-grade a video for mood", "fix washed-out After Effects renders", "gamma shift", "Rec.709 vs sRGB", "colors shifted after rendering", or "match preview to final video". Covers palette construction, gradients, perceptual interpolation (OKLCH/Lab), grading order, and video/render color management.

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Build GraphRAG retrieval pipelines on Neo4j using the neo4j-graphrag Python package (v1.22.0+). Covers retriever selection (VectorRetriever, HybridRetriever, VectorCypherRetriever, HybridCypherRetriever, Text2CypherRetriever, ToolsRetriever), external vector DB retrievers (Weaviate, Pinecone, Qdrant), retrieval_query Cypher fragments, query_params, filters, GraphRAG pipeline wiring (GraphRAG + LLM + prompt), all LLM providers (OpenAI, Anthropic, Gemini/VertexAI, Bedrock, Cohere, Mistral, Ollama), embedder setup, index creation, token usage tracking, Cypher 25 SEARCH clause, and LangChain/LlamaIndex integration. Does NOT handle KG construction — use neo4j-document-import-skill. Does NOT handle plain vector search — use neo4j-vector-index-skill. Does NOT handle GDS analytics — use neo4j-gds-skill. Does NOT handle agent memory — use neo4j-agent-memory-skill.

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Analyze images, websites, and Figma files to extract their design and generate a `design.md` with token system, component inventory, and reconstruction notes. Use this skill whenever the user wants to understand, document, replicate, or audit the design of something visual: a screenshot, a URL, a Figma link, a Pinterest reference, a mockup, a competitor's site, a component, a dashboard, a landing page. Also when they ask 'extract the design system from X', 'document the style of Y', 'analyze this visually', 'convert this image into tokens', 'help me replicate this design', 'what palette does this site use', 'how is this built'. Also for single elements: 'copy this navbar', 'recreate this illustration', 'give me a prompt to regenerate this graphic' — element mode outputs a focused element.md, with token-grounded image-model prompts when the element is visual art. If the user brings any visual source and wants to understand it at a design level — this skill should activate.

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The Execution Trader's procedure for turning an approved ticket into one Hyperliquid action and reconciling it - the pre-send checklist, order construction rules, single-send discipline, unknown-result handling and the execution report. Use before and after every send, cancel, modify, leverage change or close.

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Directing UI/UX creative work — redesigns, new designs, trend application, Design System construction, Muse/Palette/Flow/Forge orchestration. Use for design direction. Offers a co-design pair mode.

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Build Blender mesh surfaces directly from extracted 2D contours/masks instead of approximate primitives. Use for 1:1 mascot/logo reconstruction, exact leaf/petal silhouettes, filled wireframe shapes, shallow bas-relief forms, or when the model outline must match a front template before adding depth.

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Segment overlapping visual parts from source images, wireframes, texture atlases, and decals before mesh reconstruction. Use when a mascot/logo/template contains touching or overlapping components and exact structural part masks are needed before contour-to-mesh, UV fitting, or landmark repair.

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UV unwrap, atlas-map, project textures, use alpha decals, bake maps/lightmaps, and prepare texture-driven Blender assets for glTF/GLB export. Use whenever the user provides texture packs, texture atlases, decals, UV layouts, lightmaps, wants a texture to fit a mesh 1:1, or reports stretched/off textures. Pairs with reference-to-3d for template-accurate reconstruction and blender-materials for PBR values.

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Drive Blender from natural language: create or edit 3D models, materials, lighting, cameras, renders, animation, and exports through Blender MCP. Route complete scenes to domain skills and wireframe/reference requests to reconstruction skills. Also use for 3D requests that do not name Blender. Requires a configured official or ahujasid MCP backend.

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Build a five-level rubric with coherent logic for a learning target within a developmental band. Use for Manning methodology programmes where Competent = success. For general curriculum rubrics, use criterion-referenced-rubric-generator instead.

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Run a Meta-Harness-style optimization loop NATIVELY — automatically search over the scaffolding around a FIXED base model (memory, retrieval, context construction, prompt templates, summarization, tool-selection logic) by proposing candidate variants, scoring each on a cheap deterministic eval, and keeping a Pareto frontier of quality vs cost — using native Agent / Workflow / loop tools instead of a standalone Python harness. Use this whenever the user wants to optimize, evolve, tune, distill, or search over a harness, scaffold, prompt system, memory or retrieval policy, context-assembly code, or summarizer while keeping the model fixed; whenever they mention Meta-Harness, harness optimization, scaffold evolution, automatic prompt/memory optimization, an evolutionary or Pareto search over candidate implementations, or "make the harness/agent better without retraining"; and whenever the gain must come from the code AROUND the model rather than the model weights. Reproduces the Meta-Harness paper's method natively, with no claude_wrapper.py and no metered solver API.

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Advanced CV for infrastructure inspection including forest fire detection, wildfire precondition assessment, roof inspection, hail damage analysis, thermal imaging, and 3D Gaussian Splatting reconstruction. Expert in multi-modal detection, insurance risk modeling, and reinsurance data pipelines. Activate on "fire detection", "wildfire risk", "roof inspection", "hail damage", "thermal analysis", "Gaussian Splatting", "3DGS", "insurance inspection", "defensible space", "property assessment", "catastrophe modeling", "NDVI", "fuel load". NOT for general drone flight control, SLAM, path planning, or sensor fusion (use drone-cv-expert), GPU shader development (use metal-shader-expert), or generic object detection without inspection context (use clip-aware-embeddings).

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Manage construction contract administration from the field perspective. Covers AIA contract forms (A101, A201, A401), bond types and requirements, mechanics lien law, insurance verification, indemnification, dispute resolution, and subcontractor default procedures. Provides practical field guidance for notice requirements, lien waiver processing, COI verification, and claims documentation. Integrates with pay-application (lien waivers), change-order-tracker (constructive changes), delay-tracker (notice provisions), sub-performance (default triggers), and cost-tracking (back-charges). Triggers: "contract", "contract admin", "AIA", "A201", "A101", "bond", "performance bond", "payment bond", "lien", "lien waiver", "mechanics lien", "insurance", "COI", "certificate of insurance", "OCIP", "CCIP", "indemnification", "dispute", "mediation", "arbitration", "notice", "cure notice", "default", "sub default", "termination for cause", "claims", "ConsensusDocs", "EJCDC".

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Query the BuildAI PostgreSQL database (read-only). Returns results as JSON for construction project data — projects, RFIs, submittals, budgets, change orders, daily logs, punch lists, insurance, vendors, pay applications.

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Formally verify construction payment bonds by extracting fields from bond documents and cross-referencing against Treasury Circular 570, state licensing, and underwriting limits. Use whenever the user uploads a payment bond PDF, mentions bond verification, asks "is this bond valid", references AIA A312, or needs to verify a surety company's authority to write bonds. Also trigger on "verify bond", "check surety", "payment bond", "performance bond", or "Circular 570."

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Microsoft 365 と現場コックピットの情報を統合し、現場ごとの優先順位と次アクションを助言する。 Use when ユーザーが「今日何を優先すべき」「現場横断で次のアクションを教えて」と依頼したとき。

Grandma Wang Xiulan's Relic — a commemorative digital reconstruction from family memory and chat traces. 奶奶·王秀兰的 Relic

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Contrapuntal writing and analysis covering species counterpoint, fugue structure, canon types, and imitative techniques. Covers Fux's five species, cantus firmus construction, consonance and dissonance treatment, invertible counterpoint, fugue anatomy (subject, answer, countersubject, episode, stretto), canon varieties, and contrapuntal practice from Palestrina through Shostakovich. Use when writing or analyzing counterpoint, studying fugue structure, or understanding the linear dimension of polyphonic music.

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Practical argument analysis and construction -- how to identify, evaluate, reconstruct, and build real arguments in natural language. Covers argument identification (premises, conclusions, intermediate steps), charity and steel-manning, argument mapping, the distinction between deductive validity and inductive strength, burden of proof, and the rhetorical context in which arguments operate. Use when the goal is to engage with real-world argument rather than to formalize it.

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Historical argumentation, evidence-based writing, and oral history methods. Covers thesis development for historical arguments, evidence selection and deployment, counterargument construction and rebuttal, historical writing conventions, and the methodology of oral history as both source and practice. Use when constructing historical arguments, writing analytical essays, conducting oral history interviews, or assessing the quality of historical writing.

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Computational thinking as a problem-solving discipline independent of programming languages. Covers the four pillars (decomposition, pattern recognition, abstraction, algorithm design), computational problem-solving methodology (understand, decompose, generalize, formalize, verify), abstraction levels (from hardware through user interface), modeling and simulation, automata and formal languages (DFA, NFA, regular expressions, context-free grammars, Turing machines), computational complexity classes (P, NP, NP-complete, undecidable), and constructionist pedagogy (learning by building, Logo, Scratch, physical computing). Use when approaching unfamiliar problems, teaching problem-solving strategies, analyzing problem complexity, or bridging between domain knowledge and computational solutions.

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Three-dimensional art and sculptural thinking for art education. Covers additive and subtractive sculptural processes, armature construction, modeling in clay, carving principles, casting and moldmaking, assemblage and found-object sculpture, installation art as expanded sculpture, and the conceptual transition from pictorial to spatial thinking. Use when working with three-dimensional media, analyzing sculptural form, understanding spatial composition, or investigating the relationship between sculpture and site.

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Color theory principles for art education. Covers the three color properties (hue, saturation, value), color mixing systems (subtractive and additive), color relationships (complementary, analogous, triadic, split-complementary), color temperature, simultaneous contrast and the relativity of color perception, and practical palette construction. Use when analyzing color in artworks, planning color schemes, understanding optical phenomena in painting, or investigating Albers's Interaction of Color experiments.

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。