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Found 128 Skills
Systematic debugging methodology with root cause analysis. Phases: investigate, hypothesize, validate, verify. Capabilities: backward call stack tracing, multi-layer validation, verification protocols, symptom analysis, regression prevention. Actions: debug, investigate, trace, analyze, validate, verify bugs. Keywords: debugging, root cause, bug fix, stack trace, error investigation, test failure, exception handling, breakpoint, logging, reproduce, isolate, regression, call stack, symptom vs cause, hypothesis testing, validation, verification protocol. Use when: encountering bugs, analyzing test failures, tracing unexpected behavior, investigating performance issues, preventing regressions, validating fixes before completion claims.
Run conversion rate optimization through hypothesis-driven testing including audit, hypothesis generation, test design, statistical analysis, and rollout decisions. Use this skill whenever the user wants to optimize conversion, run A/B tests, audit a funnel, generate test hypotheses, design experiments, or analyze test results. Triggers on conversion optimization, CRO, A/B test, split test, multivariate test, hypothesis, conversion funnel, funnel audit, experiment design, statistical significance, lift, optimization. Also triggers when the user has a conversion problem and isn't sure where to start, or when test results are ambiguous and need interpretation.
Investment thesis tracker — maintains and updates the investment thesis for portfolio holdings and watchlist names by continuously tracking key data points (revenue growth, gross margin, user metrics), catalyst progress (new products, expansion, policy), and risk milestones, then renders a verdict on whether the thesis still holds. Triggers: "投资逻辑", "Thesis追踪", "投资假设", "逻辑验证", "跟踪持仓", "买入逻辑", "持仓理由", "投資邏輯", "Thesis追蹤", "投資假設", "邏輯驗證", "追蹤持倉", "investment thesis", "thesis tracking", "investment hypothesis", "thesis validation", "thesis check", "investment rationale", "position monitoring", "thesis intact", "is my thesis still valid".
Guides management consulting-style work—engagement framing, hypothesis-driven problem structuring, issue trees, business cases, operating model and capability design, strategic options analysis, workshop facilitation, and executive recommendations (not legal advice). Use when diagnosing a business problem, structuring a strategy or transformation initiative, building a business case for leadership, designing target operating models, preparing steerCo or board recommendations, or advising on build-vs-buy and portfolio priorities—not for detailed requirements/BRDs (business-analyst), multi-team delivery tracking (technical-program-manager), contract negotiation (commercial-counsel), revenue accounting (senior-revenue-accountant), applied AI architecture (applied-ai-architect-commercial-enterprise), or system ADRs (senior-system-architecture). Canvas/TAM: business-model-researcher. Comms: communication-lead. M&A closing: transaction-manager. M&A principal/IC: transaction-principal.
Autonomous NeMo-RL research agent workflow for directed hypothesis testing and open-ended discovery. Guides agents through the full experiment lifecycle: understanding recipes and environments, wiring RL or NeMo-gym runs, launching reproducible baselines and iterations, analyzing results, preserving human oversight, and using git plus TSV logs as the research ledger.
Statistical modeling toolkit. OLS, GLM, logistic, ARIMA, time series, hypothesis tests, diagnostics, AIC/BIC, for rigorous statistical inference and econometric analysis.
Improve activation, retention, and engagement through hypothesis-driven growth experiments.
Systematic debugging methodology — binary search isolation, hypothesis-driven debugging, reproducing issues, and root cause analysis. Use when debugging errors, unexpected behavior, or test failures.
Design enrichment columns that bridge research hypotheses to list enrichment. Two modes: segmentation (columns that score hypothesis fit per company) and personalization (columns for company-specific hooks). Interactive column design with the user. Outputs ready-to-run column_configs for list-enrichment. Triggers on: "data points", "enrichment columns", "column design", "what to research", "data point builder", "build columns", "segmentation columns", "personalization columns".
Debug a broken Zoom integration by isolating the failure point and routing into the right Zoom references. Use when auth, API, webhook, SDK, or MCP behavior is failing and you need a ranked hypothesis list plus verification steps.
Conduct statistical hypothesis testing including null/alternative hypothesis formulation, p-values, Type I/II errors, and test statistic selection. Use this skill when the user needs to determine whether a result is statistically significant, choose the right statistical test, interpret p-values correctly, or evaluate research findings — even if they say 'is this result significant', 'which statistical test should I use', or 'what does this p-value mean'.
Use when diagnosing unexpected behavior, failed workflows, bugs, browser or Node.js runtime issues, logs, traces, or when preparing a root-cause hypothesis. 诊断异常、定位 bug、判断修复方向时使用：先建立证据表，区分运行时事实和代码推断，避免多层猜测；证据不足时添加 copy-friendly 浏览器日志或本地 Node.js JSONL 日志。