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You are a cloud cost optimization expert specializing in reducing infrastructure expenses while maintaining performance and reliability. Analyze cloud spending, identify savings opportunities, and implement cost-effective architectures across AWS, Azure, and GCP.
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Ensure designs specify failure modes, timeouts, error contracts, and observability for critical flows.
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Ensure designs define operability basics: SLO/SLI, monitoring, alerting, on-call actions, and incident handling expectations.
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Ensure architecture docs define RPO/RTO, failover paths, data consistency, and DR drillability.
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Ensure event-driven designs specify delivery guarantees, ordering, idempotency, schema evolution, and replay/backfill strategy.
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Ensure code changes keep logs/metrics/traces useful for debugging failures and regressions.
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Find missing tests for critical paths, edge cases, and failure handling in changed code.
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Detects patterns that make tests flaky and proposes stabilization steps.
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Evaluate and improve an existing Claude Code skill using explicit success criteria and small controlled changes. Use when the user asks to optimize a skill, reduce over-triggering or under-triggering, improve reliability, tighten instructions, or add evals for a skill. Also trigger on "スキルを改善して", "スキルを最適化して", "スキルの品質を確認して".
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Evidence-driven application audit protocol for security, authorization, privacy, concurrency, state integrity, reliability, performance, accessibility, visual consistency, responsive behavior, and release readiness. Use for incremental checks, pre-merge review, pre-launch audits, high-stakes deep audits, AI-generated code review, hardening, or release-gate design. Prefer this protocol over ad-hoc review when the user asks whether software is safe or ready to ship.
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Use this skill whenever the user asks to inspect, audit, review, assess, or evaluate a codebase/project for maintainability, extensibility, architecture, reliability, security, testing, engineering quality, or AI-agent/prompt/tooling risks. Also use this when invoked by `/inspect`. It performs a read-only, evidence-backed, multi-agent project inspection with complete file coverage, per-dimension scoring, blunt technical findings, and explicit degraded-mode disclosure.
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Master error handling patterns across languages including exceptions, Result types, error propagation, and graceful degradation to build resilient applications. Use when implementing error handling, designing APIs, or improving application reliability.
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Define and implement Service Level Indicators (SLIs) and Service Level Objectives (SLOs) with error budgets and alerting. Use when establishing reliability targets, implementing SRE practices, or measuring service performance.
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Master advanced prompt engineering techniques to maximize LLM performance, reliability, and controllability in production. Use when optimizing prompts, improving LLM outputs, or designing production prompt templates.
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Testing and benchmarking LLM agents including behavioral testing, capability assessment, reliability metrics, and production monitoring—where even top agents achieve less than 50% on re...
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Optimize multi-agent systems with coordinated profiling, workload distribution, and cost-aware orchestration. Use when improving agent performance, throughput, or reliability.
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Master error handling patterns across languages including exceptions, Result types, error propagation, and graceful degradation to build resilient applications. Use when implementing error handling, designing APIs, or improving application reliability.
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Choose and compare cloud design patterns for distributed systems. Use when reviewing architecture, selecting workload patterns, or mapping reliability, performance, messaging, security, and migration concerns to concrete design options.
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Expert en chaos engineering (Gremlin, Litmus, fault injection, game days, fiabilité)
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Master advanced prompt engineering techniques to maximize LLM performance, reliability, and controllability.
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Parallel read-only multi-agent review of a current git diff or explicit file scope to find behavioral regressions, security or privacy risks, performance or reliability issues, and contract or test coverage gaps. Use when the user asks for a review swarm, parallel review, diff review, regression review, security review, or wants high-signal issues plus a prioritized fix path without editing files.
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Use when: analysing a project's debug and reliability health — inline markers, logging hygiene, and error handling.
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Senior engineering analyst for code review, plan review, and automation review. Four-lens review covering architecture, code quality, reliability, and performance, each scored 1-10. Delivers APPROVE, REVISE, or REJECT verdicts. Use when you need a code review, plan review, quality check, or want to verify work before shipping. Part of the architect-system loop. Reads from system/blueprints/ and source code. Outputs to system/reviews/.
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Senior engineering analyst for code review, plan review, and automation review. Use when: (1) "review this", "analyze the code", "check this plan", (2) After implementation to verify quality, (3) "is this good enough?", (4) Before marking a task complete, (5) Reviewing a blueprint from /architect, (6) Reviewing output from /refinery. Four-lens review: architecture, code quality, reliability, performance. Reads from system/blueprints/ and source code. Outputs to system/reviews/.
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