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概要と使いどころ
Structures portfolio review with strategic fit assessment, divestiture candidate identification, and proceeds redeployment analysis. Use when reviewing corporate portfolios, identifying divestiture candidates, or planning asset dispositions.
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Adjusts reported earnings for non-recurring items, accounting policy choices, and run-rate normalizations. Use when performing QofE analysis, adjusting EBITDA, or validating seller financial presentations.
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。
Constructs proprietary factor definitions with signal specification, universe application, and orthogonalization methodology. Use when defining custom factors, creating proprietary signals, or building factor libraries.
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。
Constructs plan of reorganization models with debt-for-equity conversion, new money injection, and emergence capital structure. Use when modeling restructuring plans, designing emergence capital structures, or analyzing plan feasibility.
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。
Constructs risk parity allocation with equal risk contribution, leverage optimization, and asset class volatility targeting. Use when building risk parity, equalizing risk contribution, or designing leveraged balanced portfolios.
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。
Constructs stat arb strategies with pair selection, signal generation, and portfolio optimization under market neutrality constraints. Use when building stat arb models, designing market-neutral strategies, or optimizing pair portfolios.
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Quantifies revenue and cost synergies with build-up methodology, realization timelines, and integration cost offsets. Use when estimating deal synergies, modeling cost savings, or building synergy cases for IC.
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。
Evaluates geographic expansion strategies with market entry sequencing, localization requirements, and international unit economics. Use when analyzing expansion plans, assessing international readiness, or modeling geo-expansion costs.
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Evaluates IG bond market conditions with spread analysis, maturity curve optimization, and investor demand assessment. Use when advising IG issuers, analyzing credit spreads, or timing IG bond offerings.
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Evaluates dividend policy with payout sustainability, peer comparison, and investor preference analysis across growth and value contexts. Use when analyzing dividend policy, evaluating payout ratios, or designing dividend programs.
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。
Evaluates non-traditional securitization collateral including solar, data centers, digital infrastructure, and IP royalties. Use when analyzing esoteric ABS, evaluating non-standard collateral, or structuring novel asset classes.
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 whenever writing, reviewing, or debugging .NET/C# code that uses the BallisticCalculator NuGet package (namespace BallisticCalculator) or its Gehtsoft.Measurements unit types — even when the user doesn't name the package explicitly but is clearly doing external/interior ballistics in .NET (bullet drop, velocity, energy, windage, spin drift, time of flight, zeroing a scope) for rifles, air rifles, bows, or artillery. Covers the full public API (Ammunition, Rifle, Atmosphere, Wind, ShotParameters, TrajectoryCalculator, TrajectoryPoint); standard, custom, .drg, and multi-BC drag tables; saving/loading data and building your own file format around it (BXml and System.Text.Json serialization); and building or rendering scope reticles (e.g. to SVG). Also use it for this library's Gehtsoft.Measurements Measurement<T> unit types (DistanceUnit, VelocityUnit, AngularUnit, WeightUnit, PressureUnit, …). Skip for: generic physics or projectile-motion exercises, a different ballistics library (e.g. GNU/JBM), game-engine or Unity projectile motion, plain unit conversions, and non-code ballistics questions (load-data or forensics advice). Self-contained: no access to the library source or binaries is required — prefer this over scanning the package to rediscover the API. Describes 1.1.13+, including the named ZeroRangeCantBeReachedException / TrajectoryCannotBeCalculatedException failures.
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。
GEO+SEO audit of asdlc.io — analyzes the codebase for Generative Engine Optimization across AI citability, technical infrastructure, content quality, schema markup, and knowledge base discoverability. Produces a composite GEO Score (0-100) with prioritized action plan.
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。
Integrates shadcn/ui into React apps generated from Stitch designs. Component discovery and installation, token alignment with Stitch design system, customization patterns, and blocks (auth, dashboard, sidebar). Use with stitch-react-components or stitch-nextjs-components.
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。
Provides Mermaid diagram syntax, best practices, and styling rules for technical visualizations. Use when creating diagrams, flowcharts, sequence diagrams, class diagrams, state diagrams, ER diagrams, architecture diagrams, C4 diagrams, or any visual documentation in markdown.
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。
Hunt authentication and authorization bypasses — forced browsing, path traversal in auth, header injection, JWT downgrade, OAuth state confusion, role manipulation. Use when an endpoint returns 401/403 but appears reachable.
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。
Hunt GraphQL-specific vulns — introspection abuse, field-level authorization (IDOR), batched queries for brute force, alias-based rate limit bypass, deep query DoS, mutation injection, schema disclosure, suggestion leakage, CSRF via GET, and CSRF via POST without preflight. Use when a GraphQL endpoint is present.
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 or improve data visualizations, charts, and data presentation interfaces. Use when the user asks to add charts, build dashboards, visualize data, choose chart types, make data accessible, or present metrics and analytics.
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。
Clarify priority and emphasis by fixing unclear primary actions, competing visual weight, loud section titles, and weak label/value treatment. Use when the user mentions hierarchy, prioritization, too much competition, grayscale confusion, loud headings, or unclear primary actions.
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。
Orchestrates SDD project initialization — version detection, environment verification, scaffolding, and git setup.
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 after EZ_math_model coding has produced src/*.py and before packaging when code quality, reuse, vectorization, naming, or unnecessary complexity should be reviewed without changing behavior.
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Step 2 of the PaperOrchestra pipeline (arXiv:2604.05018). Execute the visualization plan from outline.json — render plots and conceptual diagrams from experimental_log.md and idea.md, optionally refine via VLM critique loop, and produce context-aware captions. Runs in parallel with the literature-review-agent. TRIGGER when the orchestrator delegates Step 2 or when the user asks to "generate the figures for my paper" or "render the plots from this experiment log".
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。
Find the most valuable commercial insight and the monetization point closest to lawful revenue for a project, product, service, website, community, content account, open-source tool, or business idea. Use when a user asks how to monetize, who pays, why people do not buy, what to charge, whether to keep building, what to stop, what to do next, or asks to continue or deepen an earlier business analysis. Answer the user's actual question before asking for more information and carry the analysis forward without repeating it. When the buyer, purchased result, or delivery ability is unknown, do not select them from industry stereotypes; use explicit conditional candidates and an evidence-gathering next step. Not for investment advice, income forecasts, get-rich-quick schemes, or guaranteed results.
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。
Class interfaces present one cohesive abstraction - don't mix domain logic with serialization, persistence, or unrelated concerns
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。