'modeling' 검색 결과

Analyzes intraday volatility dynamics with open/close effects, lunch-time patterns, and event-driven volatility estimation. Use when modeling intraday volatility, timing order execution, or analyzing time-of-day effects.

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Builds recovery waterfall models with absolute priority, secured vs unsecured claims, and plan of reorganization distribution analysis. Use when modeling bankruptcy recoveries, analyzing claim priorities, or estimating creditor distributions.

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Builds carry waterfall models with preferred return hurdles, catch-up provisions, and clawback mechanics across deal-by-deal and whole-fund structures. Use when modeling carry economics, comparing waterfall structures, or analyzing GP incentive alignment.

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Builds carbon credit models with offset generation analysis, verification costs, and market pricing dynamics for carbon-linked investments. Use when modeling carbon credits, analyzing offset economics, or evaluating carbon market exposure.

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Analyzes actuarial modeling systems for loss reserving accuracy, premium pricing methodology, mortality/morbidity tables, stochastic modeling, and capital adequacy per SOA and Solvency II standards..

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Facilitate DDD domain modeling sessions via EventStorming conversation and DML (Domain Modeling Language). Use whenever the user wants to model a business domain by discovering domain events, commands, aggregates, policies, read models, and bounded contexts through dialogue. Produces incrementally-built DML as the primary artifact, plus a Markdown session report. Also invoke for refining existing DML, mapping out a new feature's domain model, or when the user says "ドメインモデリングしたい", "イベントストーミング", "DDDで整理したい", "DMLを育てたい".

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Power BI semantic modeling assistant for building optimized data models. Use when working with Power BI semantic models, creating measures, designing star schemas, configuring relationships, implementing RLS, or optimizing model performance. Triggers on queries about DAX calculations, table relationships, dimension/fact table design, naming conventions, model documentation, cardinality, cross-filter direction, calculation groups, and data model best practices. Always connects to the active model first using power-bi-modeling MCP tools to understand the data structure before providing guidance.

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Credit risk data cleaning and variable screening pipeline for pre-loan modeling. Use when working with raw credit data that needs quality assessment, missing value analysis, or variable selection before modeling. it covers data loading and formatting, abnormal period filtering, missing rate calculation, high-missing variable removal,low-IV variable filtering, high-PSI variable removal, Null Importance denoising, high-correlation variable removal, and cleaning report generation. Applicable scenarios arecredit risk data cleaning, variable screening, pre-loan modeling preprocessing.

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Expert data scientist for advanced analytics, machine learning, and statistical modeling. Handles complex data analysis, predictive modeling, and business intelligence. Use PROACTIVELY for data analysis tasks, ML modeling, statistical analysis, and data-driven insights.

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Create TypeScript scaffolding for a domain aggregate, a group of objects governed by shared business rules. Generate its main entity, value objects, repository interface, domain events, and unit test stubs inside an existing context.

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• Adding an aggregate to an existing domain context
• Modeling a business concept with rules to enforce
• Creating entity, repository, event, and test scaffolding

Choose tools and workflows for 3D modeling, dimensioned CAD parts, scan processing, rendering, and fabrication. Capability tables and recipes help connect tasks from photographs or initial designs to printable parts, CNC toolpaths, or game assets.

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• Plan a workflow from dimensioned CAD to 3D printing
• Model and export a game asset
• Reconstruct a 3D model from photographs

Analyze drug concentration and response data to calculate exposure, fit models of drug movement and effects, and simulate dosing schedules. Produces exploratory research results with explicit assumptions and diagnostic checks.

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• Calculate exposure and half-life from concentration data
• Compare models of drug concentration over time
• Simulate dosing schedules for research

Inspect supported local scientific files before modeling, summarize structure and missing values, and flag possible data leakage or outlier effects. Produces bounded aggregate reports with identifiers obscured and provides a structured analysis report template.

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• Check local CSV or TSV data before modeling
• Audit missing values and overlap between data splits
• Compare outlier influence and transformation sensitivity

Review code and infrastructure for security risks, map potential threats, and plan stronger defenses. The skill covers OWASP checks, attack and defense exercises, and incident response, with validation required for each environment.

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• Reviewing code and infrastructure security
• Mapping threats with STRIDE or PASTA
• Planning stronger security settings

Build three- to five-year financial projections for early-stage startups, linking revenue, expenses, hiring, and cash balances. Compare conservative, base, and optimistic scenarios, estimate how long cash will last, and model fundraising amounts and ownership dilution.

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• Build three- to five-year financial projections
• Estimate monthly cash use and remaining operating time
• Compare conservative, base, and optimistic scenarios

Assess cybersecurity risks using NIST SP 800-30 Rev 1 by examining threats, weaknesses, likelihood, and business impact. Produce a ranked risk register, a structured record of risks and recommended responses, with a summary for leadership.

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• Preparing documented risk analysis for compliance frameworks
• Assessing a new system before launch
• Reporting the highest risks to leadership

Analyze business data, test hypotheses, and build predictive models with statistical and machine learning methods. Get support across data exploration, experiment design, visualization, result validation, and planning model deployment and monitoring.

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• Analyzing customer churn and predicting customers at risk
• Designing an A/B test and evaluating its results
• Forecasting demand for inventory planning

Analyze a codebase to identify valuable assets, attack entry points, and realistic abuse paths. Produce a concise Markdown threat model that explains risk priorities, distinguishes existing protections from proposed mitigations, and makes assumptions explicit.

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• Map attack entry points in a codebase
• Assess threats within a specific project directory
• Prioritize risks to sensitive data and credentials

Analyze a codebase to identify valuable assets, attack entry points, and realistic abuse paths. Produce a concise Markdown threat model that explains risk priorities, distinguishes existing protections from proposed mitigations, and makes assumptions explicit.

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• Map attack entry points in a codebase
• Assess threats within a specific project directory
• Prioritize risks to sensitive data and credentials

Create, update, or reuse a repository threat model: a document describing its architecture, attacker capabilities, trust boundaries, and potential security failures. The result is a Markdown reference grounded in the repository's actual code and scope.

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• Documenting architecture and trust boundaries
• Creating or updating a repository threat model
• Preparing a threat model for a specific security review

Assess whether data is trustworthy enough for analysis, dashboards, experiments, or modeling. Check missing values, duplicates, consistency, freshness, and changes over time, then explain the evidence, downstream risks, likely causes, and practical fixes.

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• Check missing values and duplicate records
• Investigate sudden changes in data quality
• Reconcile conflicting sources and metric definitions

Create, update, or reuse a repository threat model: a document describing system architecture, attacker capabilities, trust boundaries, and potential security failures. Produce a Markdown model grounded in source evidence for standalone use or a security scan.

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• Creating a threat model for a repository
• Updating a model after architecture changes
• Preparing a model for a security scan

Create a Markdown threat model grounded in a codebase. Identify valuable assets, boundaries between trusted and untrusted components, realistic attack paths, and mitigations, then prioritize risks using explicit assumptions about likelihood and impact.

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• Map attack paths across a codebase
• Assess threats within a specific project directory
• Prioritize risks to data and credentials

Provides shared reference material for mathematical modeling competitions, covering writing conventions, problem-specific pitfalls, and chart guidelines. Other skills consult relevant sections during their work; this resource does not run independently.

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• Referencing competition writing conventions
• Checking pitfalls for different problem types
• Consulting chart and figure guidelines