「state」の検索結果

Analyze failed or stuck proofs and propose auxiliary lemmas to help complete the proof in Isabelle/HOL or Coq. Use when encountering proof failures, stuck proof states, unprovable subgoals, or when needing to strengthen induction hypotheses. Identifies missing lemmas, suggests proof strategies, and generates helper lemmas with appropriate statements and proof sketches. Supports inductive proofs, case analysis, rewriting, and complex proof obligations.

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Performs abstract interpretation over source code to infer possible program states, variable ranges, and data properties without executing the program. Reports potential runtime errors including out-of-bounds accesses, null dereferences, type inconsistencies, division by zero, and integer overflows. Use when analyzing code for potential runtime errors, performing static analysis, checking safety properties, or verifying program behavior without execution.

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Explain why counterexamples violate specifications by analyzing formal specifications (temporal logic, invariants, pre/postconditions, code contracts), informal requirements (user stories, acceptance criteria), test specifications (assertions, property-based tests), and providing step-by-step traces showing state changes, comparing expected vs actual behavior, identifying root causes, and assessing violation impact. Use when debugging test failures, understanding model checker output, explaining runtime assertion violations, analyzing static analysis warnings, or teaching specification concepts. Produces structured markdown explanations with traces, comparisons, state diagrams, and cause chains. Triggers when users ask why something failed, explain a violation, understand a counterexample, debug a specification, or analyze why a test fails.

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Generate test assertions from existing code implementation. Use when the user has implementation code without tests or incomplete test coverage, and needs assertions synthesized by analyzing the code's behavior, inputs, outputs, and state changes. Supports Python (pytest/unittest), Java (JUnit/AssertJ), and JavaScript/TypeScript (Jest/Chai). Handles equality checks, collections, exceptions, and state verification.

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Nuxt 5 data management with useFetch, useAsyncData, useState, and Pinia. Use when creating composables, fetching data, managing state, or debugging reactive/SSR data issues.

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Idiomatic Go concurrency - sync primitives, channel semantics, the select statement, and the standard channel patterns (cancellation/done-channel, fan-out/fan-in, pipeline, or-done, context, worker-pool). Use when writing or reviewing Go that spawns goroutines, shares state, or coordinates over channels, even if the user never says "concurrency" - e.g. data races, deadlocks, goroutine leaks, sync/context/select usage, or "make this parallel". Distilled from luk4z7/go-concurrency-guide.

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Produce formatted .xlsx financial statement workbooks from XBRL statement data. Uses Bash + openpyxl (Python) following Anthropic FSI xlsx-author conventions for professional Excel output with calculation arc cross-validation.

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Build Sankey, alluvial, river, and CONSORT-style flow diagrams to visualize cohort transitions, cell-state changes, or pipeline filtering using ggalluvial, networkD3, plotly, and consort. Use when showing how entities move between categories across timepoints (cell states, drug response classes, patient flow through a trial) or filtering pipelines (variants filtered through QC stages).

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Reconstruct ancestral states at internal phylogenetic nodes for sequences (PAML codeml, IQ-TREE --ancestral, GRASP, FastML), discrete traits (corHMM hidden-rate Markov, ape::ace, phytools::make.simmap stochastic mapping, BayesTraits), and continuous traits (phytools::fastAnc, geiger Brownian/OU, RPANDA). Use when designing constructs for ancestral protein resurrection, tracing trait evolution along a tree, performing stochastic character mapping, testing models of trait evolution (BM vs OU vs EB), inferring ancestral genome content via Dollo or DTL reconciliation, or quantifying ancestral-state uncertainty for downstream comparative analyses.

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Production-grade TypeScript reference for React & Next.js frontend development. Covers type narrowing, component Props, generic hooks, discriminated unions, as const, satisfies, Zod validation, TanStack Query, server/client boundaries, forms, state management, performance, accessibility, debugging, and code review. Use when the user works with TypeScript in React or Next.js: type errors, Props design, generics, API typing, SSR/CSR boundaries, hydration issues, form validation, state management, performance, or code review. Also use for "how should I type this?", "why does this type error happen?", or any architectural decision involving TypeScript in a frontend context.

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Use when the user wants to design, redesign, shape, critique, audit, polish, clarify, distill, harden, optimize, adapt, animate, colorize, extract, or otherwise improve a frontend interface. Covers websites, landing pages, dashboards, product UI, app shells, components, forms, settings, onboarding, and empty states. Handles UX review, visual hierarchy, information architecture, cognitive load, accessibility, performance, responsive behavior, theming, anti-patterns, typography, fonts, spacing, layout, alignment, color, motion, micro-interactions, UX copy, error states, edge cases, i18n, and reusable design systems or tokens. Also use for bland designs that need to become bolder or more delightful, loud designs that should become quieter, live browser iteration on UI elements, or ambitious visual effects that should feel technically extraordinary. Not for backend-only or non-UI tasks.

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cheat-on-skill 的首次 onboarding。盘点用户能力（现有技能/可迁移底子/学历经验/每周可学时间/能坚持几个月/学习能力自评/地区/目标薪资/转型紧迫度），判定起点档位，创建 .skill-state.json 状态文件，是 skill-scan / skill-plan 的前置。触发词："能力盘点"/"我想转AI相关工作"/"找AI时代高薪工作"/"skill init"/"职业转型初始化"。**当用户想找/规划 AI 时代工作但 .skill-state.json 不存在时，先路由到此。**

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cheat-on-skill 的陪跑进度 skill。用户问“今天该干嘛”“我现在做到哪了”“继续学”“打卡”“我卡住了”“下一步是什么”时触发。读取 .skill-state.json 的 active.progress 和 learning_plan，给当天任务、检查完成情况、记录进度、根据快慢调整计划。前置：已有 .skill-state.json 且 active.learning_plan 存在。

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Evaluates a property across three investment strategies — Buy & Hold, BRRRR, and Fix & Flip — with feasibility scores, multi-year projections, tax benefits, and break-even analysis

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Mortgage Calculator & Affordability Analysis — monthly payments, amortization, loan comparison, affordability limits, rent vs buy, and refinance break-even with rate comparison tables

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Estimates rental income from comparable rentals, builds a full expense model, calculates cash flow and key investment metrics across conservative, moderate, and optimistic scenarios

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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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Generates MLS-ready property listing descriptions with attention-grabbing headlines, feature highlights, neighborhood context, and SEO keywords across multiple buyer-persona styles

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Finds and analyzes 5-10 comparable recent sales to estimate fair market value, calculate price adjustments, and score the property's value proposition

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Commercial Property Analysis — NOI, cap rate, expense ratio, tenant mix, vacancy, debt coverage, replacement cost, and lease analysis with Commercial Score (0-100)

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Neighborhood Analysis — schools, crime, walkability, demographics, amenities, growth trajectory, and natural disaster risk with Neighborhood Score (0-100)

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Fix-and-Flip Analysis — purchase price, ARV, rehab budget breakdown, holding costs, selling costs, profit margin, ROI, timeline, and risk assessment with Flip Score (0-100)

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Launches 5 parallel AI agents to produce a comprehensive property analysis with composite Property Score (0-100), investment grade, and actionable recommendations

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Transform vague product ideas into evidence-anchored problem statements for PRD v0.1 Spark. Triggers on starting new products/features, validating market opportunities, drafting PRD Why sections, or requests like "frame the problem", "define pain points", "write problem statement", "start v0.1", "what problem are we solving". Outputs structured problem tables with CFD evidence IDs.

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