「modeling」の検索結果

Analyzes asset lifecycle planning systems for capital expenditure forecasting, replacement scheduling, total cost of ownership modeling, depreciation tracking, and facility condition assessments using IFMA standards and Facility Condition Index scoring..

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 construction project management software for budget tracking accuracy, earned value management (EVM) formula correctness, risk factor modeling, schedule-cost integration, change order workflow completeness, and early warning detection..

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。

Analyzes infrastructure costs at 1K-100K user scales by reading the actual codebase, auto-detecting cloud providers, modeling per-action costs, and projecting total monthly spend with optimization recommendations.

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 agricultural climate risk systems for weather impact modeling, crop insurance, drought/flood prediction, soil moisture, and carbon tracking. Triggers: 'assess crop climate risk', 'evaluate weather yield models', 'review crop insurance integration'.

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Audit credit risk modeling software for scoring algorithm accuracy, regulatory compliance (ECOA, FCRA, SR 11-7), bias and disparate impact testing, model governance lifecycle, and explainability..

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Write a threat model document. Use when the user says "threat model", "threat modeling", "STRIDE analysis", "attack surface analysis", "security design review", "what are the threats to this system", "adversarial analysis", "identify threats", "security threat assessment", or needs to systematically identify and document threats to a system or feature - even if they don't explicitly say "threat model".

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Run exploratory data analysis on a dataset and produce a structured report. Use when the user says "explore this dataset", "EDA on X", "analyze this data", "what's in this dataset", "summarize this data", "first look at the data", "understand this dataset before modeling", "data quality check", "describe this dataframe", or wants to understand a new dataset before building models or dashboards.

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Use this skill when configuring FSC financial planning objects, designing periodic review cycles, modeling risk assessment workflows, or tracking goal progress in Financial Services Cloud. Trigger keywords: FinancialGoal, FinancialPlan, goal tracking, risk tolerance, review cycle, financial planning workflow, Discovery Framework, Revenue Insights. NOT for wealth management process discovery — use admin/wealth-management-requirements. NOT for Action Plan template mechanics — use admin/fsc-action-plans.

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Use this skill to define, document, and validate KPI metrics for CRM Analytics — covering metric formula design, dimension selection, target-dataset modeling, benchmark setting, and the KPI register that must exist before any dashboard or lens is built. Trigger keywords: KPI definition CRM Analytics, analytics metric design, analytics target attainment, CRM Analytics measures vs dimensions, analytics benchmark. NOT for laying out the dashboard or lens itself — use admin/analytics-dashboard-design. NOT for scoping data sources, audiences, and drill-down paths — use admin/analytics-requirements-gathering.

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 a project needs shared terminology, glossary updates, ADRs, clearer domain language, or when user language conflicts with existing code, ticket, board, project, workflow, or CONTEXT.md terms.

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Design, implement, and review XState v5 state machines and @xstate/react integrations in TypeScript. Use when modeling finite workflows, async actors, statecharts, guarded transitions, delayed transitions, actor systems, or machine-driven React behavior.

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Apply these opinionated TypeScript conventions whenever writing or reviewing TypeScript: branded types for domain modeling, discriminated unions for state, `satisfies` over `as`, const objects instead of enums, type-only imports, and the strict tsconfig baseline beyond `strict: true`. Also use for monorepo project references and incremental build setup.

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Design or change dygo Entity metadata, Fields, Record Collections, links, naming, routes, indexes, and constraints. Use when a business data model or metadata contract is the main task.

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 or extend a dygo Business App using the supported project layout, generators, metadata, SDK, and validation workflow. Use for general app work that is not primarily Entity modeling, access, hooks, Jobs, fixtures, or patches.

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。

Comprehensive guide for creating software diagrams using Mermaid syntax. Use when users need to create, visualize, or document software through diagrams including class diagrams (domain modeling, object-oriented design), sequence diagrams (application flows, API interactions, code execution), flowcharts (processes, algorithms, user journeys), entity relationship diagrams (database schemas), C4 architecture diagrams (system context, containers, components), state diagrams, git graphs, pie charts, gantt charts, or any other diagram type. Triggers include requests to "diagram", "visualize", "model", "map out", "show the flow", or when explaining system architecture, database design, code structure, or user/application flows.

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Chief Security Officer mode. Infrastructure-first security audit: secrets archaeology, dependency supply chain, CI/CD pipeline security, LLM/AI security, skill supply chain scanning, plus OWASP Top 10, STRIDE threat modeling, and active verification. Two modes: daily (zero-noise, 8/10 confidence gate) and comprehensive (monthly deep scan, 2/10 bar). Trend tracking across audit runs. Use when: "security audit", "threat model", "pentest review", "OWASP", "CSO review".

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。

Neo4j best practices for Cypher query optimization, graph data modeling, indexing, and safe execution of LLM-generated Cypher

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。

dbt best practices for SQL modeling, testing, and analytics engineering workflows

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Routes data engineering tasks to the correct DE expert agent. Use when user requests data pipeline design, DAG authoring, SQL modeling, stream processing, or warehouse optimization.

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。

dbt Core/Cloud data transformations, testing, documentation, and CI/CD. Activate on: dbt, data transformation, analytics engineering, ref, source, staging model, mart, dbt test. NOT for: orchestration/scheduling (use airflow-dag-orchestrator), data warehouse tuning (use data-warehouse-optimizer).

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。

Safe database migration manager for zero-downtime DDL changes and rollback plans. Activate on: database migration, schema change, DDL, rollback plan, zero-downtime migration, Prisma migrate, Drizzle kit, Flyway, column rename, table alter. NOT for: query optimization (use database-optimizer), ORM modeling (use data-pipeline-engineer), backup/restore (use devops-automator).

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。

Snowflake, BigQuery, clustering, partitioning, and materialized views for warehouse performance. Activate on: Snowflake, BigQuery, Redshift, query optimization, clustering, partitioning, materialized view, warehouse cost, query profile. NOT for: dbt model structure (use dbt-analytics-engineer), data modeling (use dimensional-modeler).

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。

Expert data engineer for ETL/ELT pipelines, streaming, data warehousing. Activate on: data pipeline, ETL, ELT, data warehouse, Spark, Kafka, Airflow, dbt, data modeling, star schema, streaming data, batch processing, data quality. NOT for: API design (use api-architect), ML training (use ML skills), dashboards (use design skills).

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。

Model organizations as BDI systems with filtered perception, discourse-shaped desires, accommodations, and abstraction-level hierarchy. Use for socio-technical coordination and organizational modeling. NOT for mechanistic workflows, individual psychology, or non-social domains.

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。