「struct」の検索結果

PowerPoint generation for construction: project updates, stakeholder presentations, progress reports, bid presentations. Automated slide creation with charts and data.

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 4D construction simulations by linking BIM elements to project schedules. Generate time-based visualizations, sequence analysis, and construction phasing with Gantt 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。

Calculate carbon footprint of construction projects. Estimate CO2 emissions from materials, transportation, and construction processes using emission factors databases.

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。

Design data models for construction projects. Create entity-relationship diagrams, define schemas, and generate database structures.

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。

Extract structured data from construction specifications. Parse CSI sections, requirements, submittals, and product data from spec documents.

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。

Forecast project outcomes using historical data: cost overruns, schedule delays, risk probabilities. Machine learning models for construction prediction.

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 SQL queries for construction databases. Generate optimized SQL queries for construction data retrieval

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 structured construction meeting minutes. Track action items, decisions, and attendees.

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 data evolution patterns in construction organizations. Assess digital maturity and data strategy for construction companies

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。

Guide to OpenConstructionERP: architecture, modules, API surface and quick start. Use when starting any OpenConstructionERP work, onboarding a user to the platform, or deciding which module/endpoint to use.

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Field operations in OpenConstructionERP: punch list, daily diary, HSE observations and task tracking on site. Use when automating construction site workflows (deficiencies, diaries, safety, site tasks).

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。

Access and utilize open construction pricing databases. Match BIM elements to standardized work items, calculate costs using public unit price databases with 55,000+ work items.

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。

Check construction AI systems against the EU AI Act (Regulation 2024/1689): classify risk of estimation, scheduling, CV and agent tools, document transparency, keep human oversight. Use when deploying or auditing AI in construction.

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 and analyze geometric clashes in BIM models. Identify MEP, structural, and architectural conflicts before construction.

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。

Material passports and circular construction: generate per-element material inventories from BOQ/BIM, mark reuse potential and recycled content, and prepare deconstruction data. Use for circular-economy and EU Taxonomy-aligned projects.

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Property development lifecycle in OpenConstructionERP: lead to SPA to handover — feasibility, budgeting from cost bases, sales tracking and construction handover. Use for residential/commercial development projects.

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This skill should be used when the user asks to "create a plot arc", "story structure", "add a plot point", "story timeline", "track foreshadowing", "pacing", "sagging middle", "act structure", "story arc", "plot outline", "snowflake method", or wants to plan and manage the narrative structure of a story. It owns book-level pacing; NOT for the craft of scene outcomes or chapter hooks, which this skill only plans in the outline (use scene-craft), or a pacing check as a revision pass (use revision-continuity).

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Detects PII in unstructured data including emails, documents, images, and logs using NER-based detection with spaCy and Microsoft Presidio, regex patterns, OCR integration, and confidence scoring. Keywords: PII detection, unstructured data, NER, spaCy, Presidio, OCR, regex, email scanning, document scanning.

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。

Restructure existing code without changing its behavior, through a test-gated refactoring loop: a named target, a green suite over that target before any edit, a planned sequence of small named refactorings, and the full suite re-run after every step. Use when the user wants to refactor, restructure, clean up, simplify, or improve the design of existing code, or to apply refactoring recommendations from a code-review or architectural-analysis report. This skill changes code; it does not review code (use code-review), assess architecture (use architectural-analysis), plan a multi-module restructure before executing it (use plan-a-change), map domain boundaries before restructuring along them (use ddd-analysis), or build new behavior test-first (use tdd). Do not use it on code inside an active tdd loop; the refactor step of tdd owns that cleanup. Runs its planned sequence to completion without pausing for review; to review each named refactoring as it lands, use pairing.

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。

Audit and organize AI coding-agent instructions, including AGENTS.md, CLAUDE.md, skills, and agent definitions. Use when the user asks to diagnose conflicting instructions, excessive approval pauses, broad skill triggers, duplicate guidance, or broken instruction references, or to clean up that instruction set. Ordinary code review, Markdown editing, or application debugging alone does not trigger this workflow. Inspection stays read-only; apply changes when authorized.

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。

Convert image references into spatial hypotheses, camera constraints, construction routes, material evidence, and measurable Blender reconstruction gates. Use whenever a user asks to replicate, recreate, match, clone, or reconstruct a scene, environment, object, material, lighting setup, or shot from one or more images, especially when room connectivity, hidden space, perspective, visible-frame fidelity, material identity, aging, wetness, or photographic treatment matters.

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。

Think and work like an expert Cryo-EM Structural Biologist. Use when a task calls for Cryo-EM Structural Biologist judgment. Reasons from vitrified specimens, CTF-modulated projections, particle heterogeneity, FSC validation, local resolution, preferred orientation, and map-model fit before making structural claims.

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。

Access and analyze AlphaFold protein structure predictions. Use when predicted structures are needed for proteins without experimental structures, or for confidence scores (pLDDT).

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。

Structure prediction using Boltz-1/Boltz-2, an open biomolecular structure predictor. Use this skill when: (1) Predicting protein complex structures, (2) Validating designed binders, (3) Need open-source alternative to AF2, (4) Predicting protein-ligand complexes, (5) Using local GPU resources. For QC thresholds, use protein-qc. For AlphaFold2 prediction, use alphafold. For Chai prediction, use chai.

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。