Results for “regression-metric”

LLM output evaluation — automated metrics, LLM-as-judge, A/B testing, regression testing. Use when measuring LLM output quality, comparing prompt or model versions, building an automated eval pipeline, setting up regression tests for prompt changes, or evaluating RAG systems and bias/safety.

Provides a formal evaluation framework for Claude Code sessions, implementing eval-driven development (EDD) principles to define pass/fail criteria, measure reliability with pass@k metrics, and create regression test suites.

Calculate portfolio risk metrics including VaR, CVaR, Sharpe, Sortino, and drawdown analysis. Use when measuring portfolio risk, implementing risk limits, or building risk monitoring systems.

Every metric encodes an opinion about which mistake hurts.

Computes the Recall metric using torchmetrics, including configuration for binary, multiclass, and multilabel tasks.

Monitor portfolio risk, R-multiples, and position limits. Creates hedging strategies, calculates expectancy, and implements stop-losses. Use PROACTIVELY for risk assessment, trade tracking, or portfolio protection.

`analysis-agent`/`task-agent`/`review-agent`: use for recurrence guards on known defects, incidents, or escaped failures; skip speculative risk without a prior failure mechanism.

Econometrics skill for panel data models. Activates when the user asks about: "panel data", "fixed effects", "random effects", "Hausman test", "within estimator", "between estimator", "two-way fixed effects", "clustered standard errors panel", "FE model", "RE model", "pooled OLS", "unobserved heterogeneity", "panel regression", "first difference estimator", "entity fixed effects", "time fixed effects", "面板数据", "固定效应", "随机效应", "豪斯曼检验", "双向固定效应", "面板回归", "个体效应", "时间效应", "一阶差分"

Calculates SaaS health metrics like ARR, MRR, churn, LTV, and CAC from raw business numbers, benchmarks them against industry standards, and provides prioritized actionable advice.

Econometrics skill for panel data models. Activates when the user asks about: "panel data", "fixed effects", "random effects", "Hausman test", "within estimator", "between estimator", "two-way fixed effects", "clustered standard errors panel", "FE model", "RE model", "pooled OLS", "unobserved heterogeneity", "panel regression", "first difference estimator", "entity fixed effects", "time fixed effects", "面板数据", "固定效应", "随机效应", "豪斯曼检验", "双向固定效应", "面板回归", "个体效应", "时间效应", "一阶差分"

Build the funnel metrics that actually get trusted. Stage-by-stage conversion, velocity, win rate, and the single biggest leak, with every definition pinned so nobody relitigates the numbers in the meeting. Built for B2B RevOps teams, customizable to your CRM and your stage model. Trigger on "build my funnel metrics", "what's my conversion by stage", "where's the leak", "what's our win rate", "how fast do deals move", or any funnel diagnostic.

Econometrics skill for Regression Discontinuity Design (RDD). Activates when the user asks about: "regression discontinuity", "RDD", "RD design", "sharp RDD", "fuzzy RDD", "running variable", "forcing variable", "cutoff", "bandwidth selection", "local linear regression", "McCrary test", "density test", "RDROBUST", "continuity assumption", "donut hole RDD", "geographic RDD", "断点回归", "回归不连续", "运行变量", "截断值", "带宽选择", "精确断点", "模糊断点", "密度检验", "局部线性回归"

Evaluate and rank agent results by metric or LLM judge for an AgentHub session.

Design a comprehensive product metrics dashboard with key metrics, data sources, visualization types, and alert thresholds.

Run metric-driven iterative optimization loops -- define a measurable goal, run parallel experiments, measure each against hard gates or LLM-as-judge scores, keep improvements, and converge on the best solution. Use when optimizing clustering quality, search relevance, build performance, prompt quality, or any measurable outcome that benefits from systematic experimentation.

Evaluates machine-generated log summaries without human-written references, using LLM judgment and dense embeddings to score relevance, informativeness, and coherence.

Evaluate and rank agent results by metric or LLM judge for an AgentHub session. Use when the user runs /hub:eval or asks to score, compare, or pick a winner among completed AgentHub agents.

Layer 4 of the keyword research pipeline. Spawns a "skeptical SEO" adversarial sub-agent to argue against every survivor of Layers 1-3. Catches mechanical-classifier blind spots — wrong SERP intent, hidden link-graph gauntlets, AIO trajectory shifts, vanity-rank metrics. Same pattern as quality-check's adversarial draft read, applied to keyword selection.

Econometrics skill for Regression Discontinuity Design (RDD). Activates when the user asks about: "regression discontinuity", "RDD", "RD design", "sharp RDD", "fuzzy RDD", "running variable", "forcing variable", "cutoff", "bandwidth selection", "local linear regression", "McCrary test", "density test", "RDROBUST", "continuity assumption", "donut hole RDD", "geographic RDD", "断点回归", "回归不连续", "运行变量", "截断值", "带宽选择", "精确断点", "模糊断点", "密度检验", "局部线性回归"

Choose and audit startup metrics using the Lean Analytics framework: separate actionable metrics from vanity metrics, identify the One Metric That Matters for your business model and stage, set targets, and plan instrumentation.

Evaluate and rank agent results by metric or LLM judge for an AgentHub session.

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Comprehensive results analysis for empirical research: generate publication-quality descriptive statistics and balance tables, interpret regression coefficients with economic magnitude and effect sizes, assess identification assumption diagnostics, and produce structured results memos. Use when asked to create summary statistics, Table 1, balance tests, interpret results, assess economic significance, or write results narratives.

Expert en métriques SaaS (MRR, ARR, churn, LTV, CAC, cohort analysis, unit economics)

Econometrics skill for OLS regression and linear models. Activates when the user asks about: "run OLS", "linear regression", "ordinary least squares", "interpret regression results", "heteroskedasticity", "multicollinearity", "regression assumptions", "robust standard errors", "GLS", "WLS", "fit a regression model", "check regression diagnostics", "OLS假设", "最小二乘法", "线性回归", "回归系数", "残差检验", "异方差", "多重共线性", "普通最小二乘", "稳健标准误", "回归诊断"

Expert in building Retrieval-Augmented Generation systems. Masters embedding models, vector databases, chunking strategies, and retrieval optimization for LLM applications.

Design telemetry systems, define KPIs, analyze player behavior data, and set up dashboards for data-driven game design decisions. Use when instrumenting a game for analytics or interpreting player data. Also trigger for "game telemetry", "player analytics", "game metrics", "KPIs", "player retention", "funnel analysis", or "player behavior".

Evaluates the robustness and alignment with human judgment of reference-based and reference-free evaluation metrics for machine translation and summarization, particularly under adversarial conditions.

Query resource usage metrics for Railway services. Use when user asks about resource usage, CPU, memory, network, disk, or service performance like "how much memory is my service using" or "is my service slow".

Design product metric trees, North Star metrics, input metrics, and instrumentation needs.

Computes the Receiver Operating Characteristic (ROC) metric using torchmetrics, supporting binary, multiclass, and multilabel tasks.