「projections」の検索結果

Evaluates demand forecasts for toll roads, airports, and ports with independent engineer review and scenario sensitivity analysis. Use when analyzing traffic studies, validating demand forecasts, or stress testing revenue projections.

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Constructs LBO models with sources/uses, debt schedules, operating projections, and returns analysis across entry/exit scenarios. Use when modeling leveraged buyouts, calculating sponsor returns, or analyzing leverage capacity.

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Audit RuField tests, trust boundaries, privacy projections, and evidence promotion. Use for conformance review, security regression review, release validation, or checking whether field accuracy claims have support.

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。

Spring Data JPA entity design, repository patterns, query methods, JPQL, Flyway/Liquibase migrations, and N+1 avoidance. Apply on Spring Boot projects with spring-boot-starter-data-jpa. Pairs with spring-boot-plugin:spring-conventions and java-foundation:java-conventions. Use this skill to: - Design JPA entities with proper annotations, ID strategy, and lazy loading. - Write JpaRepository interfaces with derived query methods and JPQL @Query. - Avoid N+1 queries using @EntityGraph or JOIN FETCH. - Manage schema evolution with Flyway or Liquibase. - Project query results with Spring Data Projections and DTOs. Do NOT use this skill for: - Service or controller patterns — see spring-boot-plugin:spring-conventions. - Build tool setup — see java-foundation:build-tooling. - Test slices (@DataJpaTest) — see java-foundation:jvm-testing.

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Trace a Proto UI change through authoritative spec lifecycle, legacy explanation, dated context, implementation, executable evidence, package surfaces, and public projections. Use before deciding scope, changing behavior, reviewing a pull request, or investigating drift.

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Independently review a Proto UI change against current authority, bounded scope, executable evidence, projections, provenance, and integration conditions. Use for pull-request review, acceptance review, pre-merge audit, or fresh-context verification. Do not use to approve one's own work.

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Create or update a readable Proto UI legacy-contract projection for explanation or an explicitly accepted uncataloged gap. Use for internal contract prose, migration banners, rationale, or synchronized readable projections. Do not use when an applicable spec entity already owns the rule or when semantics are unsettled.

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Audit an already completed protected Proto UI publication and reconcile immutable external facts with Version entities, release records, and public projections. Use after publication for registry, tag, GitHub Release, asset, checksum, workflow-head, and deployment evidence. Never republish or replace immutable evidence.

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"Build three-statement financial models (Income Statement, Balance Sheet, Cash Flow) with revenue forecasting, assumption management, and scenario analysis. Use this skill when the user needs to project financials, build a fundraising model, create financial projections for a business plan, or evaluate M&A targets — even if they say 'build a financial model', 'project our revenue', 'how much money will we make next year', or 'model this acquisition'.".

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"Build Discounted Cash Flow (DCF) valuation models to estimate intrinsic value. Use this skill when the user needs to value a company, evaluate an investment, estimate fair share price, or build financial projections — even if they say 'what is this company worth', 'should we acquire them', or 'build me a valuation model'.".

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。

D3.js data visualization — selections, data joins, scales, axes, shapes, transitions, force layouts, geo projections, framework integration

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Spring Boot 4 data layer implementation for Domain-Driven Design. Use when implementing JPA or JDBC aggregates, Spring Data repositories, transactional services, projections, or entity auditing. Covers aggregate roots with AbstractAggregateRoot, value object mapping, EntityGraph for N+1 prevention, and Spring Boot 4 specifics (JSpecify null-safety, AOT repositories). For DDD concepts and design decisions, see the domain-driven-design skill.

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Use the Skmtc CLI to scaffold projects, install or clone generators from JSR, configure schema sources and enrichments, and produce code artifacts from an OpenAPI v3 or GraphQL SDL schema. Teaches the workspace mental model (`<root>/.skmtc/<project>/`, client.json, bundle, manifest) and the agent contract (strict text / strict JSON modes, exit codes, recipe errors, `agent-context` + `doctor`); the command surface itself is discovered from the binary — `skmtc --help`, `skmtc <cmd> -h` — rather than carried in this skill. Use this skill when the user asks to "run skmtc", "generate code from an OpenAPI schema", "install a skmtc generator", "scaffold a skmtc project", "watch a skmtc project", "configure enrichments", "publish a stack", "deploy to skmtc-hub" (the command is `publish`; there is no `deploy`), "skmtc in CI", or invokes any CLI subcommand. For *authoring* a generator package (Projections, Snippets, transform functions), defer to `skmtc-generator`. When something is broken (no output, wrong output, error messages, a failed bundle build), verify before proposing a fix: read the manifest and the parse issues, and reproduce the failure first.

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Translating coarse global climate projections to local scales — dynamical vs statistical downscaling, bias correction, and added value.

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Produce and interpret PCA, t-SNE, UMAP, and PHATE plots for high-dimensional omics data with rigor about which method preserves what (variance, local structure, manifold, transitions), hyperparameter sensitivity, and the well-documented limits of 2D embeddings. Covers PCA biplot/scree/loadings, t-SNE PCA initialization (Kobak-Berens 2019), UMAP n_neighbors/min_dist trade-offs, and the Chari-Pachter 2023 critique. Use when visualizing high-dimensional data — bulk PCA, single-cell embeddings, multi-omics integration projections.

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Save, load, update, delete, merge, and navigate entity objects using TMS Aurelius ORM (TObjectManager). Use when the user asks how to persist or retrieve data with Aurelius, manage object lifetime, work with associations or collections at runtime, handle transactions, use cached updates, or control concurrency. Does NOT cover query DSL or criteria/projections (those are in a separate skill). Triggers on requests like "save an entity with Aurelius", "load a customer from the database", "add items to a collection", "how do I update an object", "flush changes", "delete a record with Aurelius", "merge a transient object", "how do transactions work in Aurelius", "batch updates Aurelius".

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Message queues, pub/sub, event sourcing with Kafka, RabbitMQ, Redis Streams. Activate on: event-driven, message queue, pub/sub, Kafka, RabbitMQ, event bus, async messaging, dead letter queue. NOT for: CQRS projections (use cqrs-event-sourcing-architect), real-time WebSocket (use websocket-realtime-expert), observability (use observability-apm-expert).

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[Content] Use when you need to evaluate business idea viability: Business Model Canvas, financial projections, risk matrix, go-to-market, execution plan.

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Use when the user asks to "allocate my influencer budget", "optimize spend across tiers", or "compare budget scenarios"; produces a tier/platform/content allocation table, ROI and CPM/CPE projections, scenario comparisons, and mid-campaign reallocation moves. Not for building the full campaign plan — use campaign-planner. 达人预算分配/投放预算优化

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Build comprehensive 3-5 year financial models with revenue projections, cost structures, cash flow analysis, and scenario planning for early-stage startups.

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 detailed 3-5 year financial model with revenue, costs, cash flow, and scenarios

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Build read models and projections from event streams. Use when implementing CQRS read sides, building materialized views, or optimizing query performance in event-sourced systems.

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Build, analyze, repair, and audit finance three-statement models and operating forecasts. Use when the user invokes $kelly-finance, asks for 财务三表, 三表模型, income statement, balance sheet, cash flow statement, forecast model, budget model, financial projections, FP&A model, SaaS/unit economics forecast, fundraising model, board finance pack, investor model, model checks, balance-sheet balancing, cash runway, working capital, capex/depreciation schedules, debt schedules, scenario/sensitivity cases, or Excel/Sheets-ready finance outputs.

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Extracts the WACC, assumptions, and DCF projections from the markdown metadata file and converts them into a clean, structured JSON file for the frontend interactive viewer.

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。