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Found 50 Skills
Create a Google Docs post-mortem, schedule a Google Calendar review, and notify via Chat.
Production incident response procedures for Python/React applications. Use when responding to production outages, investigating error spikes, diagnosing performance degradation, or conducting post-mortems. Covers severity classification (SEV1-SEV4), incident commander role, communication templates, diagnostic commands for FastAPI/ PostgreSQL/Redis, rollback procedures, and blameless post-mortem process. Does NOT cover monitoring setup (use monitoring-setup) or deployment procedures (use deployment-pipeline).
Gain wisdom from setbacks — Go through the 5-step interactive reflection (Setback → Automatic Output → Old Weights → New Parameters → Alternative Action), move from "emotional review" to "behavioral training", and update the L3 weights of your first reactions. Use when Wang Jianshuo reflects on a personal setback, mistake, or recurring pattern (reflection, post-mortem review, review, draw lessons, learn from a setback, gain wisdom, "I messed up again", "Why does this keep happening?", "Why do I always…?", "I can't just let it go", "I know the principles but can't put them into practice"). For the user as a human, not for Claude's task post-mortems.
Investigates completed DEX sandwich-style MEV from public blocks and bundles—front-victim-back ordering on EVM and Solana, Jito bundle traces, swap decoding, victim slippage vs searcher profit estimates, and evidence-style case studies. Use when the user asks for sandwich attack analysis, MEV sandwich post-mortems, high-slippage swap forensics, or searcher clustering—not for building sandwich bots, mempool manipulation for profit, or harassing labeled wallets.
Bug → spec protocol. When a bug is found or a test fails, trace the cause, decide whether a new §V invariant would catch recurrence, append to §B. This is the one non-obvious thing SDD does that plan-then-execute doesn't. Triggers on test failure, bug report, post-mortem, or explicit user ask.
Document solved problems for team reuse. Provides process knowledge for /ia-compound. Use when documenting a resolved issue, writing up lessons learned, capturing a post-mortem, adding to the knowledge base, or building searchable institutional knowledge after debugging.
Help users run effective post-mortems and retrospectives. Use when someone is reviewing a project that succeeded or failed, wants to establish learning practices, is dealing with failure aftermath, or needs to improve team learning loops.
Use when reviewing, scoring, or auditing third-party SaaS / vendor relationships — running a vendor scorecard, tracking SLA compliance, classifying third-party risk, preparing a tier-1 vendor review, or auditing the SaaS portfolio. Triggers on "vendor SLA", "vendor scorecard", "third-party risk", "TPRM", "vendor review", "SaaS audit", "supplier performance", "vendor health check", "renewal review". Forks context so large vendor catalogs (50-500 line items) and SLA logs don't pollute the parent thread. Ships 3 stdlib-only Python tools (vendor scorer with industry tuning, SLA compliance tracker with credit-claim flags, vendor risk classifier across 4 risk vectors), 3 reference docs each citing 7+ authoritative sources (Gartner / Shared Assessments / NIST / ISO 27036 / breach post-mortems), and a 5-vendor catalog template. Distinct from c-level-advisor/general-counsel-advisor (contract law, not operational management), business-growth/contract-and-proposal-writer (outbound proposals, not inbound vendor scoring), and sibling procurement-optimizer (spend categorization, not vendor performance).
Expert SRE incident responder specializing in rapid problem resolution, modern observability, and comprehensive incident management. Masters incident command, blameless post-mortems, error budget management, and system reliability patterns. Handles critical outages, communication strategies, and continuous improvement. Use IMMEDIATELY for production incidents or SRE practices.
Use when managing Ralph orchestration loops, analyzing diagnostic data, debugging hat selection, investigating backpressure, or performing post-mortem analysis
Run blameless post-mortems and retrospectives with root-cause analysis and action tracking.
Use when writing or editing prose for humans - blog posts, articles, essays, memos, announcements, release notes, post-mortems, narrative documentation. Use when output sounds like corporate-speak, contains hedging or filler adverbs, stacks abstract nouns, opens with throat-clearing, or feels generic and voiceless.