「program」の検索結果

Design loss control programs. TRIGGERS - Use when user needs help with insurance-loss-control related tasks.

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 producer training programs. TRIGGERS - Use when user needs help with insurance-producer-training related tasks.

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。

Insurance program review, coverage adequacy testing, contractor insurance verification, builder's risk/OCIP/CCIP evaluation, and property tax escrow management for AM, PM, and Development.

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 claims advocacy programs. TRIGGERS - Use when user needs help with insurance-claims-advocacy related tasks.

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。

Plan fleet insurance programs with vehicle management. TRIGGERS - Use when user needs help with fleet-insurance-plan related tasks.

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。

Manage Allstate insurance with Drivewise and Milewise 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。

Query the Bear EHR database using the semantic layer. Use when asked about clients, billing, appointments, insurance, clinical data, procedures, scheduling, programs, staff, vitals, diagnoses, revenue, claims, or any data question about the Bear application.

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 and run OKR program — company objectives, team key results, cascade design, and quarterly review cadence. Use when asked to "design our OKRs", "are our OKRs good", "cascade goals to teams", or "run a quarterly OKR 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。

Operations reconnaissance — audit process documentation, vendor contracts, compliance posture, OKR health, and cross-functional friction points to understand where operations is the bottleneck. Use when asked to "audit our operations", "where are we slow", "what processes are broken", or "before designing a compliance program".

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 a dependency scanning program — CVE detection, license checks, and CI gates. Use when asked to "scan our dependencies", "set up CVE detection", or "add a dependency CI gate".

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。

Real-world problem formulation, mathematical abstraction, and applied mathematics for translating between practical problems and mathematical frameworks. Covers the modeling cycle (problem identification, assumptions, formulation, analysis, validation, interpretation), Polya's framework adapted for modeling, common model types (linear, exponential, logistic, periodic, power-law), dimensional analysis (Buckingham Pi theorem), optimization (linear programming, gradient descent, constraint satisfaction), probability models (Markov chains, queuing theory, Monte Carlo simulation), statistical modeling (regression, hypothesis testing, model selection), model criticism (overfitting, underfitting, sensitivity analysis), and real-world case studies. Use when formulating mathematical models, performing dimensional analysis, optimizing systems, running simulations, or evaluating model validity.

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。

Assessing anthropogenic environmental impacts — pollution pathways, habitat destruction and fragmentation, land-use change, invasive species, overharvest, and extinction debt. Covers environmental impact assessment (EIA) methodology, exposure-effect relationships, population viability analysis, IPAT and ecological footprint frameworks, and strategic environmental assessment. Use when quantifying or forecasting human impacts on ecosystems, designing monitoring programs, or evaluating a proposed intervention against a baseline.

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。

Computational thinking as a problem-solving discipline independent of programming languages. Covers the four pillars (decomposition, pattern recognition, abstraction, algorithm design), computational problem-solving methodology (understand, decompose, generalize, formalize, verify), abstraction levels (from hardware through user interface), modeling and simulation, automata and formal languages (DFA, NFA, regular expressions, context-free grammars, Turing machines), computational complexity classes (P, NP, NP-complete, undecidable), and constructionist pedagogy (learning by building, Logo, Scratch, physical computing). Use when approaching unfamiliar problems, teaching problem-solving strategies, analyzing problem complexity, or bridging between domain knowledge and computational solutions.

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。

Algorithms and data structures from first principles through advanced analysis. Covers sorting (bubble, insertion, selection, merge, quick, heap, radix), searching (linear, binary, BFS, DFS, Dijkstra, A*), fundamental data structures (arrays, linked lists, stacks, queues, hash tables, trees, heaps, graphs, tries), complexity analysis (Big-O, Big-Omega, Big-Theta, amortized), recurrence relations, and algorithm design paradigms (divide-and-conquer, greedy, dynamic programming, backtracking). Use when analyzing, selecting, implementing, or comparing algorithms and data structures.

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。

Foundational skills for Zephyr RTOS development. Covers essential Embedded C patterns (BIT, CONTAINER_OF), real-time concurrency primitives (mutexes, semaphores, spinlocks), hardware literacy (datasheet-to-DTS mapping), and defensive programming. Trigger when writing core application logic, drivers, or troubleshooting foundational behavior.

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。

Formal verification of Rust programs via translation to Coq/Rocq.

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。

Forth/Factor/Joy: stack-based concatenative programming where composition replaces application.

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。

Detects timing side-channel vulnerabilities in cryptographic code. Use when implementing or reviewing crypto code, encountering division on secrets, secret-dependent branches, or constant-time programming questions in C, C++, Go, Rust, Swift, Java, Kotlin, C#, PHP, JavaScript, TypeScript, Python, or Ruby.

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。

Hedges' 4-kind lattice for bidirectional programming - covariant/contravariant/invariant/bivariant types with GF(3) correspondence

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。

Performs initial binary triage by surveying memory layout, strings, imports/exports, and functions to quickly understand what a binary does and identify suspicious behavior. Use when first examining a binary, when user asks to triage/survey/analyze a program, or wants an overview before deeper reverse engineering.

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。

Artificial Life atlas covering open-ended evolution, chemical reaction networks, morphogenesis, self-replication, and programmable chemistry. Use when picking a simulation framework, wiring ALife models into the skill graph, or onboarding contributors to the ALife cluster.

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 AddressSanitizer to detect memory safety bugs in C/C++ programs. Identifies use-after-free, buffer overflow, memory leaks, and other memory errors.

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。

Browser automation CLI for AI agents. Use when the user needs to interact with websites, including navigating pages, filling forms, clicking buttons, taking screenshots, extracting data, testing web apps, or automating any browser task. Triggers include requests to "open a website", "fill out a form", "click a button", "take a screenshot", "scrape data from a page", "test this web app", "login to a site", "automate browser actions", or any task requiring programmatic web interaction.

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 creating or updating the project skill discovery config — generates or regenerates .dh/skill_discovery.yaml by scanning the repo to infer tech stack, inventorying installed skills via npx skills list, loading candidate skill content before suggesting, and writing a config-driven skill injection file. Triggers on /dh:setup-skill-discovery invocations and programmatic --auto calls from add-new-feature Phase 3.

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。