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Review an executed business decision against its original success and stopping criteria. Compare actual results, revisit assumptions and dissenting views, and create a retrospective record with lessons and follow-up actions.
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Production incident response - from detection through resolution to post-mortem. Effective communication, systematic investigation, and blameless learning from failuresUse when "incident, outage, production issue, site down, on-call, post-mortem, war room, severity, pages, alerts, rollback, incident, outage, on-call, post-mortem, production, reliability, SRE, communication" mentioned.
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Conduct a blameless post-mortem analysis after an incident. Build timeline reconstruction, identify contributing factors, and generate actionable improvements. Focus on systemic issues rather than individual blame. Use after any production incident or service degradation, following a near-miss, when investigating recurring issues, or to share systemic learnings across teams.
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Create a structured review after a production incident, focusing on systems and processes without blaming individuals. Reconstruct events, quantify impact, investigate causes, and document specific follow-up actions with named owners and deadlines.
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Prepare an incident review by creating a Google Docs report template, scheduling a review meeting in Google Calendar, and notifying the team through Chat. The template covers the summary, timeline, root cause, and action items.
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Interactive system flow tracing across CODE, API, AUTH, DATA, NETWORK layers with SQLite persistence and Mermaid export. Use for security audits, compliance documentation, flow tracing, feature ideation, brainstorming, debugging, architecture reviews, or incident post-mortems. Triggers on audit, trace flow, document flow, security review, debug flow, brainstorm, architecture review, post-mortem, incident review.
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Blameless post-mortem structure, incident timeline reconstruction, response evaluation, and organizational learning
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Guide incident response from detection to post-mortem using SRE principles, severity classification, on-call management, blameless culture, and communication protocols. Use when setting up incident processes, designing escalation policies, or conducting post-mortems.
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Translate technical security work into the language of non-security audiences — board, executives, engineering, customer success, customers, legal, procurement, sales. Covers incident communication, post-mortem narrative, audit-findings-for-stakeholders, risk justification, security spend justification, and customer-facing breach disclosure. Use when the user mentions 'security comms,' 'communicate this finding,' 'explain to my boss,' 'board update,' 'executive summary,' 'incident communication,' 'breach notification,' 'customer disclosure,' 'security memo,' 'post-mortem narrative,' 'risk justification,' 'why this matters to the business,' 'translate this finding,' 'stakeholder update,' or has technical security work that needs to land with a non-security audience.
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Generate operations runbooks and post-mortems for incident response — severity matrix, decision trees, escalation paths, war room setup (Slack/Zoom), status page updates, customer comms templates, and blameless post-mortems with action items.
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Adversarial thinking partner for founders and executives. Stress-tests plans, prepares for brutal board meetings, dissects decisions with no good options, and forces honest post-mortems. Use when a plan needs hard scrutiny, a board meeting is coming, a painful decision has been avoided, or a failure needs an honest post-mortem.
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システムログを分析してエラーの根本原因を特定し、段階的に深堀りしていくデバッグ専門家スキル。 アプリケーションログ、システムログ、クラウドサービスログなど様々な形式に対応。 5 Whys、タイムライン分析、Fishbone分析などのRCA（根本原因分析）手法を用いて 問題の本質を突き止め、再発防止策まで提案する。 Use when analyzing system logs to find error root causes, debugging application issues, or performing technical post-mortem analysis with log data. For organizational incident management processes (post-incident review, corrective action plans, incident reports without log data), use incident-rca-specialist instead. Triggers: "analyze this log", "find the root cause", "debug this error", "why is this failing", "log analysis", "what caused this crash", "troubleshoot this issue"
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Respond to production incidents systematically with triage, investigation, resolution, and post-mortem analysis to minimize downtime and prevent recurrence. Use when handling production outages, triaging incidents, investigating critical bugs, coordinating incident response, implementing hotfixes, conducting post-mortems, or establishing incident response procedures.
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通过暂停Python执行、检查变量和跟踪代码流程来查找故障原因。可查看异常发生时的状态，也可连接正在运行的进程，调查测试失败或服务中的问题。
Challenge business plans, prepare for difficult board questions, and work through decisions with painful tradeoffs. This skill identifies assumptions and failure risks, examines stakeholder impacts, and turns postmortems into changes with clear owners and verification dates.
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Organize responses to service outages and degraded performance, from initial assessment through recovery review. Classify severity, reconstruct event timelines, draft stakeholder updates, and create response guides and follow-up actions based on incident findings.
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Design controlled failure experiments for distributed systems to examine how services recover. Produce failure injection scripts, monitoring plans, rollback procedures, and exercise guides, then turn findings into documented improvements.
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Investigate failed or stuck GSD workflows using Git history, planning documents, and file state. Produce a structured diagnostic report with evidence, detected anomalies, and recommendations to help identify causes and decide corrective actions.
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Share the current coding session transcript with the Convex team, with explicit consent, for an AI review that identifies unclear setup instructions, tooling failures, and successful patterns to help improve the quickstart system.
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Configure and collect crash dumps for modern .NET applications. USE FOR: enabling automatic crash dumps for CoreCLR or NativeAOT, capturing dumps from running .NET processes, setting up dump collection in Docker or Kubernetes, using dotnet-dump collect or createdump. DO NOT USE FOR: analyzing or debugging dumps, post-mortem investigation with lldb/windbg/dotnet-dump analyze, profiling or tracing, or for .NET Framework processes.
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Post-mortem investigation for failed GSD workflows — analyzes git history, artifacts, and state to diagnose what went wrong
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[omh] Postmortem for an outage or SLO miss: postmortems, SLOs, error budgets, incident follow-ups, and service reliability evidence. Use when the user says: reliability-review, reliability review, incident review, incident postmortem, postmortem, post-mortem, slo review, slo.
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Use when the user asks to "run a launch retro / post-mortem", "compare launch results vs targets by channel", or "decide what to keep or kill for the next launch"; produces a structured D1/W1/M1 retrospective — a per-channel actual-vs-target table (UTM-attributed own analytics as the truth column, platform self-reported numbers as reference, every figure labeled Measured / User-provided / Estimated), a 5-Whys chain on the single largest miss, keep / kill / change decisions per channel, 3-5 actionable learnings for the next launch, and an outcome snapshot submitted to the launch registry. Not for return math (CPA / ROI) — use roi-calculator; not for the stakeholder-facing report writeup — use report-generator; not for a metric deep-dive — use performance-analyzer. 发布复盘/渠道归因/5-Whys/keep-kill
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Post-mortem on what the user has already published - which posts actually worked, why, and what to stop doing. Use when the user pastes their LinkedIn analytics or past posts and asks "what's working", "why did this flop", "read my analytics", "audit my content", or wants to know what to double down on.
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