IoT-based material tracking for construction sites. Monitor material delivery, storage conditions, usage, and inventory with sensors, RFID, GPS, and real-time dashboards.
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IoT-based material tracking for construction sites. Monitor material delivery, storage conditions, usage, and inventory with sensors, RFID, GPS, and real-time dashboards.
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。
Turn sales history and current stock counts into reorder points, order quantities, and a this-week purchase list -- so a product business stops stocking out of winners and stops burying cash in losers. Handles seasonality, supplier lead times, and the dead-stock cleanup.
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。
Uses 1M context window to ingest an entire codebase and output a file-by-file migration plan. Supports JS to TS, React class to hooks, framework migrations, and more. Generates migration-plan.md with file inventory, dependency graph, migration order, file-by-file changes, estimated effort, and risk assessment.
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, create, or scaffold Ansible playbooks, roles, tasks, handlers, inventory, vars.
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Generates Records of Processing Activities automatically from IT system inventories including Active Directory, cloud service catalogs, API gateway logs, and database schemas. Covers automated field population, data flow discovery, and system-to-RoPA mapping. Activate for automated RoPA, system inventory, data discovery, auto-population, IT-driven records.
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Audit and safely repair cross-runtime Skill governance: canonical-source ownership, divergent or duplicate projections, exposure scopes and budgets, lifecycle drift, quarantine, and retirement. Use when the user explicitly requests cross-runtime or cross-scope Skill governance; ignore project-local Skill inventory, product/runtime loading or enablement checks, usage statistics, and mentions/traces.
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End-to-end app feature inventory and user-story testing workflow with a canonical tracker. Use when the user asks to audit every feature, derive expected behavior from code, test user journeys, or explicitly fix and retest documented UX or logistical defects.
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 original short videos using the 晨间收获闭环|人物巡园、连续采摘与动物回应 Creative DNA for MiniMax H3 or Seedance 2.0. Use when the user wants this causal, camera, motion, rhythm, or payoff structure with new subjects and surfaces.
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 original short videos using the 场所反制|追踪威胁与环境物件接力 Creative DNA for MiniMax H3 or Seedance 2.0. Use when the user wants this causal, camera, motion, rhythm, or payoff structure with new subjects and surfaces.
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 publishing, open-sourcing, exporting, sanitizing, or moving code, agent skills, prompts, templates, fixtures, datasets, workshop assets, or other artifacts from a private repository, vendor/runtime environment, or mixed working directory into a public repository or registry. Builds a provenance inventory, license/security review, explicit allowlist, clean staging package, approval dry run, and fresh public clone/install smoke. Triggers on "open source this", "publish these skills", "make this repo public", "export and sanitize", "подготовь публичный релиз", "выложи скиллы", "опенсорсни", "санитизируй и опубликуй". NOT for ordinary upstream bugfix PRs, vulnerability disclosure, or creating a corp-* department.
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Financial ratio analysis, profitability ratios ROE ROA ROIC, liquidity ratios current quick cash, leverage ratios debt-to-equity interest coverage, efficiency ratios asset turnover inventory turnover DSO, valuation ratios PE PB EV/EBITDA, cross-company ratio comparison, DuPont analysis
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Supply chain mapping, supplier dependency analysis, customer concentration, geographic concentration, bottleneck identification, supply chain risk, logistics network, sourcing strategy, inventory management, vertical integration analysis
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 Forestry Scientist. Use when a task calls for Forestry Scientist judgment. Reasons from silvicultural systems, site index, DGH and DBH increment, and FIA cruise design through FVS/ORGANON calibration, LiDAR area-based inventory with support matching, and IPCC carbon pools while treating site-index misassignment, plot edge effects, and change-of-spatial-support bias as first-class failure modes.
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 Energy Storage / Battery Scientist. Use when a task calls for Energy Storage / Battery Scientist judgment. Reasons from interfacial thermodynamics, ion transport, SEI/CEI dynamics, and cell engineering constraints (N/P and E/S ratio, mass loading) through galvanostatic cycling, dQ/dV, GITT and EIS/DRT, operando XRD, and PyBaMM/Newman models, while treating Li plating, lithium-inventory loss, transition-metal crossover, and coin-cell artifacts as first-class failure modes.
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Think and work like an expert Bridge Engineer. Use when a task calls for Bridge Engineer judgment. Reasons from load paths, limit states, redundancy, and durability through AASHTO LRFD rating (LRFR/inventory vs. operating), FEM grillage and OpenSees models, HEC-18 scour analysis, and NDE such as half-cell potential and phased-array UT while treating fracture-critical fatigue details, lost composite action, scour, and bearing seizure as first-class failure modes.
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Think and work like an expert Atmospheric Chemist. Use when a task calls for Atmospheric Chemist judgment. Reasons from coupled photochemical OH-NOx-VOC radical budgets, heterogeneous aerosol uptake, and NOx-limited versus VOC-limited regimes through MCM/F0AM and GEOS-Chem/CMAQ/WRF-Chem models, OH-reactivity closure, PMF on AMS factors, HYSPLIT trajectories, and EKMA isopleths while treating chamber wall losses, instrument cross-sensitivities and inlet artifacts, and emission-inventory error as first-class failure modes.
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。
Set up and deploy a Boundless prover to a GPU server using Ansible. Handles inventory setup, SSH connectivity, NVIDIA drivers, Docker, and the full bento stack. Use when deploying a new prover, redeploying to an existing server, or troubleshooting prover infrastructure.
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。
Cross-agent self-inspection of your AI-agent stack. Audits skills, MCP servers, hooks, plugins, commands, credentials, and memory files across Claude Code, Codex, OpenClaw, and NanoClaw. Produces a structured inventory and narrative briefing with cross-ecosystem risk analysis. Use when the user asks to audit their own setup, check what they have installed, review their agent stack security posture, or understand cross-tool interactions. Use when a user has accumulated skills/plugins/MCP servers over time and wants visibility into their attack surface. Use after installing new skills or plugins. Do NOT use for vetting external code before install (that is repo-forensics). Do NOT use for incident response during active attacks. Do NOT use for fixing or patching vulnerabilities (forensify is read-only).
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Local Market Analysis — median prices, inventory, days on market, price trends, rental conditions, economic drivers, and market classification with Market Score (0-100)
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Test for regulatory compliance: GDPR/CMP consent verification, Google Consent Mode v2, Global Privacy Control (GPC), CCPA/US state opt-out, EU AI Act Article 50 transparency, Better Ads Standards, and cookie-inventory auditing. Covers automated consent-flow testing, third-party script blocking before consent, and cookie drift detection. Use when: "GDPR test," "compliance," "CMP test," "cookie consent," "consent mode," "CCPA," "GPC," "AI Act," "Better Ads," "privacy banner." Not for: WCAG/axe-core test authoring — use accessibility-testing. Not for: OWASP/vuln scanning — use security-testing. Not for: evaluating your LLM feature's quality or safety — use ai-system-testing. Related: accessibility-testing, security-testing, ai-system-testing, ci-cd-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。
Configuration management and automation with Ansible. Use when the user needs to write playbooks, manage inventory, create roles, use Ansible Vault for secrets, or orchestrate multi-server deployments across environments.
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World-class game UI design expertise combining the clarity of Nintendo's UI philosophy, the immersive diegetic interfaces of Dead Space and Metroid Prime, and the competitive readability principles from esports titles. Game UI is the invisible bridge between player intent and game response. Great game UI serves the player without breaking immersion. It communicates critical information at a glance during intense action, guides new players without patronizing veterans, and adapts gracefully from 4K monitors to handheld screens and from keyboard to touch to controller. The best game UI designers understand that every pixel of screen space is sacred - borrowed from the game world itself. Use when "game ui, game interface, hud design, heads up display, game menu, inventory ui, health bar, stamina bar, game hud, minimap, crosshair, reticle, button prompt, controller ui, gamepad navigation, diegetic interface, in-world ui, quest tracker, damage numbers, cooldown indicator, radial menu, game tooltip, game-ui, hud, game-interface, game-menu, controller-ui, diegetic, game-design, accessibility, console, mobile-games" mentioned.
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 behavioral/feature documentation for web apps using code-first analysis. Reads source code via tree-sitting to produce _FEATURES.md, with optional visual verification via browser automation. Companion to tree-sitting. Use when documenting app behavior, creating feature inventories, generating behavioral ground truth for agents, or before modifying UI code. Triggers on "map features", "document app behavior", "feature inventory", "what does this app do".
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 hierarchical _FEATURES.md files that describe what a codebase DOES from a user/consumer perspective, anchored to source symbols via tree-sitting. Supports large complex codebases through feature-driven decomposition into sub-feature files. Uses a multi-pass synthesis: orientation → detail → overview rewrite. Use when someone says "what does this do", "document features", "feature inventory", "_FEATURES.md", or needs to understand a codebase's purpose before modifying it. Complements tree-sitting (structural) with semantic (why/what-for) layer.
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。