「power」の検索結果

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.

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Audit, redesign, generate, and improve IEEE manuscript figures, tables, captions, result presentation, plotting scripts, visual polish, hybrid Python/R plus vector-editor workflows, publication-ready matplotlib house style, and layout using routed visual-evidence checks. Use when checking or creating plot readability, axes, legends, line overlap, table structure, metric reporting, captions, grayscale accessibility, IEEE one-column/two-column layout, figure/table placement, claim-evidence mapping, reviewer first-impression risks, matplotlib/seaborn or ggplot2 figure code, SVG/PDF/TIFF/PNG export, Illustrator/Inkscape/PowerPoint/Figma finishing plans, or IEEE-style engineering evidence graphics.

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Draft, restructure, and diagnose IEEE-style technical manuscript sections using a routed static/dynamic workflow. Use for IEEE conference, journal, Transactions, Letters, or magazine papers when writing titles, abstracts, introductions, related work, methods, experiments, conclusions, contribution statements, section outlines, or Chinese-to-English engineering paper drafts in AI, computer science, communications, control, signal processing, electrical/electronic engineering, power, robotics, circuits, and applied systems.

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Comprehensive GitHub code review with AI-powered swarm coordination

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AI-powered multi-agent code review. Simulates a team of Principal Engineers reviewing code from different perspectives. Use when asked to review code, check a PR, analyze changes, or perform code review.

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Use when you need direct browser control - teaches Chrome DevTools Protocol for controlling existing browser sessions, multi-tab management, form automation, and content extraction via use_browser MCP tool

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Provides patterns to build declarative AI Services with LangChain4j for LLM integration, chatbot development, AI agent implementation, and conversational AI in Java. Generates type-safe AI services using interface-based patterns, annotations, memory management, and tools integration. Use when creating AI-powered Java applications with minimal boilerplate, implementing conversational AI with memory, or building AI agents with function calling.

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Use when about to claim a result, effect, significance, or that an analysis reproduces, before reporting or writing it up - requires running the analysis fresh and reading the actual output first; evidence before claims always

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Use when an analysis is complete and verified, and you need to decide how to report it and archive the work for reproducibility

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Use when you have an approved research question and need a concrete analysis plan, before touching outcome data or fitting any model

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Use when facing 2+ independent investigations that can proceed without shared state - parallel literature survey, multi-dataset replication, or pre-specified robustness checks

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Use when creating new skills, editing existing skills, or verifying skills work before deployment

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Use when your human partner has explicitly opted into exploratory or feasibility mode - a compute-heavy simulation, an unproven pipeline, an unbenchmarked solver, an untested cluster job - or when whether the work can run at all is still unknown, when a plan's largest configuration has never been executed, when a memory or wall-clock ceiling is estimated rather than measured, or when someone proposes pre-registering over runs that have never happened

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Use when you have a pre-registered analysis plan to execute inline in this session with review checkpoints, on a platform without subagents

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Use after completing an analysis or before reporting a finding, to have a skeptical reviewer attack the conclusion before you believe it

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You MUST use this before any data analysis or investigation - before exploring a dataset, loading or profiling data, running a model, computing a statistic, or testing an idea, and before any outcome data is touched

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Use when a result is surprising, impossible, contradicts a sanity check, a pipeline fails, a model won't converge, or a replication fails - before adjusting anything

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Use before running any confirmatory analysis or looking at outcome data, when testing a hypothesis, computing a p-value, or about to claim an effect - locks predictions and decision rules before results are seen

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Use when receiving critical feedback on an analysis or manuscript, before implementing suggestions, especially if feedback seems unclear or methodologically questionable - requires verification, not performative agreement or blind changes

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Use when executing a pre-registered analysis plan with mostly independent steps in the current session

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Use when starting analysis work that needs isolation, or before executing a pre-registered plan - ensures an isolated, reproducible workspace with pinned environment, fixed seeds, and immutable raw data

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

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Automate construction photo report generation using n8n with AI-powered image analysis.

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Implement semantic vector search for construction data. Build AI-powered search using embeddings and vector databases (Qdrant, ChromaDB) for intelligent querying of specifications, standards, and project 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。