5,266 件 ・ 関連度順
Verify claims, quotes, timelines, and findings against supplied source files and return a source map with verified, conflicting, not found, and manual-review statuses. Use when the user asks to fact-check a memo, audit, timeline, executive summary, research packet, or project brief against PDFs, XML, HTML, notes, screenshots, exported chat logs, or other supplied files before sending, publishing, or relying on the result.
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 latest policy analysis sweep runs (*_policy_analysis_*) by comparing episodes/summary metrics, diagnostics, and video artifacts; generate a concise markdown report and optional frame snapshots.
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。
Autonomous orchestrator that scans, refactors, and eradicates technical debt at the end of the development lifecycle to achieve a Zero Debt codebase / Orkestrator otonom untuk menghapus utang teknis sebelum rilis.
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 guidelines to refactor legacy PHP codebases into clean, modern, and scalable MVC-structured projects / Pedoman ahli untuk merefaktor codebase PHP lama menjadi proyek terstruktur MVC yang bersih, modern, dan skalabel.
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 guide for in-memory Abstract Syntax Tree (AST) code knowledge graphs, real-time symbol dependency mapping, refactoring blast radius calculation, and dead code eradication / Panduan ahli graf pengetahuan AST kode in-memory, pemetaan dependensi simbol real-time, kalkulasi radius dampak refaktor, dan pembersihan kode mati.
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。
Methodological guide for the AI Agent to safely and systematically translate, refactor, and modernize giant legacy codebases (PHP, Python 2, old React) into modern stacks.
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。
Configures integration tests with WebApplicationFactory and Testcontainers. Provides test database setup, authentication helpers, and utilities for testing API endpoints with real dependencies.
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。
Generates Domain Entities following DDD principles with factory methods, private setters, domain events, and proper encapsulation. Supports aggregate roots, child entities, and value objects.
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。
Configures structured logging with ILogger<T> and ILoggerFactory following Microsoft best practices. Includes Serilog setup, log enrichment, and logging source generators for high-performance logging.
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。
Hi-fi interactive HTML prototype — single-file, double-click-to-open, Playwright-verified. Use when asked to "make it clickable", "build a prototype", "hi-fi mockup", "interactive demo", "iOS prototype", "app mockup", "ui demo", or "prototype this". Goes beyond wireframes into visually finished, state-driven HTML with device frames and real images. Not production code — a design artifact for testing flows and pitching ideas.
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。
User research reconnaissance — survey existing personas, research docs, interview notes, and feedback artifacts to establish what is already known about users. Use when asked to "what research exists", "review existing personas", "what do we know about our users", or before starting new research or synthesis work.
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 an exact ChatGPT/Codex Plugin artifact has passed local package, brand, and listing gates and you need reviewer-ready submission evidence without confusing preparation, submission, approval, and publication states.
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。
Evidence-first expert knowledge handoff skill. Use when a founder, senior engineer, salesperson, support lead, consultant, or other domain expert is leaving, changing roles, or needs their judgment made reusable. It turns consented documents, chat, meeting notes, interviews, and explicit facts into a traceable handoff package. Trigger on requests such as: "capture this expert's judgment", "prepare a departure handoff", "make an onboarding mentor", "extract the decision rules", or "把专家经验交接下来".
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。
Prevents private infrastructure details (node hostnames, internal project names, local usernames and personal emails, absolute home paths, private and VPN IP ranges) from leaking into public repositories through commits, PRs, docs or release artifacts. Use when working in a public or soon-to-be-public repo, before commits or releases, when writing deployment docs for an OSS project, or when the user asks to "set up the privacy guard", "install privacy-guard", "check for leaks", "protect this public repo". Bootstraps a pre-commit hook backed by a gitignored local denylist plus gitleaks.
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 concepts in nutrition science — macronutrients, micronutrients, energy balance, Atwater factors, reference intakes (DRI/RDA/AI/UL), food composition tables, and the methods of human nutrition research. Grounds the rest of the department in a shared vocabulary and in the measurement limits of the field, including controlled-trial history, observational-study limits, and the biochemical basis for calorie accounting. Use when a question asks what something "is" nutritionally, how energy and nutrients are measured, or what the reference numbers mean.
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。
Provides compliance, governance, and supply chain security guidance for cloud-native systems. Covers OPA Rego policies, Kyverno cluster policies, SBOM generation, SLSA provenance, audit trail design, and regulatory framework mapping. Use when user mentions 'compliance', 'governance', 'OPA', 'kyverno', 'SBOM', 'SLSA', 'audit', 'policy-as-code', 'SOC2', 'HIPAA', 'PCI-DSS', 'artifact signing'.
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。
Symbolic manipulation, equation solving, and algebraic structures for mathematical reasoning. Covers distributive law, factoring, completing the square, linear through polynomial equation solving, systems of equations (substitution, elimination, Gaussian elimination, matrix methods), algebraic structures (groups, rings, fields), modular arithmetic, polynomial theory, and inequalities. Use when solving equations, simplifying expressions, working with algebraic structures, or performing symbolic manipulation.
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。
Statics, dynamics, stress-strain analysis, materials selection, failure modes, and finite element analysis concepts for engineered structures. Covers free-body diagrams, equilibrium, internal forces (shear and moment), beam deflection, column buckling, material properties, factor of safety, fatigue, fracture mechanics, and FEA workflow. Use when analyzing loads on structures, selecting materials, predicting failure, or interpreting structural 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。
Causal reasoning in historical analysis. Covers distinguishing immediate from underlying causes, tracing chains of causation across time scales, identifying unintended consequences, and applying counterfactual reasoning to assess causal significance. Use when analyzing why historical events occurred, evaluating the relative weight of causes, or assessing whether outcomes were inevitable or contingent.
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。
Understanding and managing what digital services collect, store, share, and infer about you. Covers password security and entropy, multi-factor authentication, privacy settings, data minimization, the difference between first-party and third-party tracking, cookies and fingerprinting, privacy laws (GDPR, CCPA), and how to respond to data breaches. Use when helping a learner make informed decisions about what to share, with whom, and under what terms.
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。
Software design principles, patterns, and architecture from SOLID through distributed systems. Covers the five SOLID principles with violations and fixes, DRY/KISS/YAGNI heuristics, separation of concerns, 12 GoF design patterns organized by intent (creational, structural, behavioral), architectural patterns (MVC, MVP, MVVM, layered, hexagonal, microservices, event-driven), coupling and cohesion metrics, dependency injection, and the design decision framework for choosing between competing approaches. Use when making design decisions, reviewing architecture, refactoring code, or teaching software engineering principles.
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。
A/B testing, randomization, sample size calculation, confounding control, and causal inference for data science. Covers the full experimental lifecycle from hypothesis formulation through power analysis, randomization strategies, blocking, factorial designs, sequential testing, and the potential outcomes framework for causal claims. Use when designing experiments, planning A/B tests, calculating sample sizes, or reasoning about causation from data.
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 the user asks "what should I work on", mentions GSD phases, ROADMAP, or .planning/ artifacts. Routes to the correct GSD command for the current project state.
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。