Failure injection patterns, blast radius control, steady state hypothesis, and gameday planning for resilience testing.
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概要と使いどころ
Failure injection patterns, blast radius control, steady state hypothesis, and gameday planning for resilience testing.
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When designing distributed systems for scalability, reliability, and consistency. Covers CAP/PACELC theorems, consistency models (strong, eventual, causal), replication patterns (leader-follower, multi-leader, leaderless), partitioning strategies (hash, range, geographic), transaction patterns (saga, event sourcing, CQRS), resilience patterns (circuit breaker, bulkhead), service discovery, and caching strategies for building fault-tolerant distributed architectures.
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 microservices architectures with service boundaries, event-driven communication, and resilience patterns. Use when building distributed systems, decomposing monoliths, or implementing microservices.
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Recovers broken agent state via crash recovery, context overflow, and merge conflict protocols. Use when an agent session fails or a worktree is corrupted.
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Applies event-driven async messaging to decouple producers and consumers. Use when designing real-time or multi-subscriber systems needing loose coupling.
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。
Implement bounded, idempotency-aware API throttling, backoff, and retry handling for 429 and transient 5xx responses.
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Use service mesh patterns for AI inference traffic management, mTLS, canary releases, policy enforcement, and cross-cluster resilience.
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Run structured AI red team exercises for jailbreak resistance, data exfiltration risk, harmful output controls, and agent tool abuse resilience.
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Use when adding retries, backoff, or concurrency limits to Spring Boot 4 / Spring Framework 7 code with core Retryable and ConcurrencyLimit support. Covers enablement, backoff, proxy limits, and behavior after retries are exhausted.
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Use when building Spring Cloud Gateway 5 on Spring Boot 4, including WebFlux or Web MVC routes, edge authentication, trusted headers, rate limits, timeouts, and resilience. Do not use for ordinary outbound HTTP clients or domain orchestration.
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Assessment of pseudonymization techniques and re-identification risk. Covers tokenization, hashing, encryption-based pseudonymization, and hybrid approaches. Includes re-identification risk scoring using the motivated intruder test, quantitative metrics (marketer, journalist, prosecutor models), and linkage attack resilience evaluation. References ENISA 2019 pseudonymization report.
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 this skill when reasoning about generative AI, adversarial machine learning, neural network security, algorithmic fairness, or deep learning fundamentals. This skill channels the thinking of Ian Goodfellow, inventor of Generative Adversarial Networks (GANs). Trigger this skill when the user asks about model robustness, mitigating bias, evaluating AI guardrails, designing generative models, or defending against adversarial attacks. Apply his frameworks of minimax games, adversarial feature learning, and worst-case robustness analysis to shift the user's perspective from average-case optimization to adversarial resilience.
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Improve interface resilience through better error handling, i18n support, text overflow handling, and edge case management. Makes interfaces robust and production-ready.
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 microservices architectures with service boundaries, event-driven communication, and resilience patterns. Use when building distributed systems, decomposing monoliths, or implementing microservices.
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。
Decision framework for isolating every external dependency in a test suite: when to use in-process mocks, HTTP stubs (MSW, WireMock), record-replay, fault injection (Toxiproxy), or ephemeral real services (Testcontainers), and how to enforce that no real calls escape in CI. Use when: "mock service," "stub API," "fake service," "WireMock," "MSW," "Toxiproxy," "test isolation," "dependency management," "stub an external API in CI." Not for: consumer-driven contract verification (Pact, broker) — use contract-testing; standing up a full Docker Compose env or seed data — use test-environments; broad resilience/game-day fault campaigns — use chaos-engineering. Related: contract-testing, test-environments, api-testing, test-data-management, chaos-engineering.
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Patterns for designing, building, and operating microservices architectures. Covers service decomposition, inter-service communication, resilience patterns, data consistency, and observability in distributed systems. Use when ", " mentioned.
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Expert at building resilient applications through proper error handling. Covers Result types, error boundaries, try-catch patterns, typed errors, and graceful degradation. Use when "error handling, try catch, error boundary, Result type, exception, error-handling, typescript, react, resilience" mentioned.
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A strict code reviewer, pair programmer, debugger, and mentor for Python, Bash, Google Apps Script, JavaScript, and Swift/Apple platforms. Use when writing, reviewing, debugging, planning, or securing code, or for senior-level rigor, a security review, or mentoring. Mode triggers — REVIEW: (critique + refactor), EXPLAIN: (teach), MVP:/PROTOTYPE: (lean-but-safe), DEBUG: (root-cause), AUDIT: (report-first); default is pair-programming. Drives a spec→plan→TDD→verify loop with a deterministic-first, verify-before-asserting (anti-hallucination) discipline. Enforces a security floor (secrets, injection, input validation, isolation, least privilege, authn) and a backup/continuity floor on a phase-aware rigor ladder (Prototype→MVP→Production) — cheap ≠ insecure. Covers testing & fuzzing, SAST/secret-scan/type-check/supply-chain gates, multi-tenant data protection, resilience & DR, scalability, CI/CD, cloud/containers/DBs, and accessible UI — deep references read on demand.
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 this skill when reasoning about generative AI, adversarial machine learning, neural network security, algorithmic fairness, or deep learning fundamentals. This skill channels the thinking of Ian Goodfellow, inventor of Generative Adversarial Networks (GANs). Trigger this skill when the user asks about model robustness, mitigating bias, evaluating AI guardrails, designing generative models, or defending against adversarial attacks. Apply his frameworks of minimax games, adversarial feature learning, and worst-case robustness analysis to shift the user's perspective from average-case optimization to adversarial resilience.
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。
Reach for this skill whenever Claude encounters situations involving supply chain innovation, B2B customer respect, community revitalization, vocational education, or navigating massive business crises. Apply the mental models of Diane Hendricks, co-founder of ABC Supply and building supplies billionaire, when users face decisions about strategic acquisitions, counter-cyclical expansion, or treating blue-collar workers as respected entrepreneurs. Use this skill to channel her 'fight or fold' resilience, her strict financial responsibility hierarchy, and her focus on solving the exact pain points you faced as a customer.
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。
Review whole motion-system release resilience.
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Phase G of a WinForms-to-Avalonia migration: decompose oversized UI state and orchestration, harden asynchronous workflows and external boundaries, preserve composition lifetimes, keep Headless tests process-isolated, and update ownership documentation. Use only when an explicit migration has post-port structural or resilience debt, or when the orchestrator routes here. Baseline input security belongs in the phase that introduces the boundary, not only here.
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Applies C# and .NET backend standards to ASP.NET Core APIs, EF Core, Dapper, and workers. Use when shaping API boundaries, data access, resilience, or observability.
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Verifying system resilience via load testing, contract testing, chaos engineering, and mutation testing. Use for limit verification, non-functional testing, or reliability validation.
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。