Search Results for "statistical" | AgentCC

data-analyst

Ailabs 393 Ai Labs Claude Skills Data Analyst

This skill should be used when analyzing CSV datasets, handling missing values through intelligent imputation, and creating interactive dashboards to visualize data trends. Use this skill for tasks involving data quality assessment, automated missing value detection and filling, statistical analysis, and generating Plotly Dash dashboards for exploratory data analysis.

data_analysis

Artificialanalysis Stirrup Data Analysis

High-performance data analysis using Polars - load, transform, aggregate, visualize and export tabular data. Use for CSV/JSON/Parquet processing, statistical analysis, time series, and creating charts.

bio-pathway-go-enrichment

Gene Ontology over-representation analysis using clusterProfiler enrichGO. Use when identifying biological functions enriched in a gene list from differential expression or other analyses. Supports all three ontologies (BP, MF, CC), multiple ID types, and customizable statistical thresholds.

bio-hi-c-analysis-hic-differential

Compare Hi-C contact matrices between conditions to identify differential chromatin interactions. Compute log2 fold changes, statistical significance, and visualize differential contact maps. Use when comparing Hi-C contacts between conditions.

bio-workflows-metabolomics-pipeline

End-to-end metabolomics workflow from raw MS data to pathway analysis. Orchestrates XCMS preprocessing, annotation, normalization, statistical analysis, and pathway mapping. Use when processing LC-MS metabolomics data.

bio-workflows-proteomics-pipeline

End-to-end proteomics workflow from MaxQuant output to differential protein abundance. Orchestrates data import, normalization, imputation, and statistical testing with MSstats or limma. Use when processing mass spectrometry proteomics.

bio-de-edger-basics

Perform differential expression analysis using edgeR in R/Bioconductor. Use for analyzing RNA-seq count data with the quasi-likelihood F-test framework, creating DGEList objects, normalization, dispersion estimation, and statistical testing. Use when performing DE analysis with edgeR.

bio-workflows-cytometry-pipeline

End-to-end flow cytometry workflow from FCS files to differential analysis. Orchestrates compensation, transformation, gating/clustering, and statistical testing with CATALYST/diffcyt. Use when processing flow or mass cytometry data end-to-end.

bio-crispr-screens-hit-calling

Statistical methods for calling hits in CRISPR screens. Covers MAGeCK, BAGEL2, drugZ, and custom approaches for identifying essential and resistance genes. Use when identifying significant genes from screen count data after QC passes.

bio-methylation-methylkit

DNA methylation analysis with methylKit in R. Import Bismark coverage files, filter by coverage, normalize samples, and perform statistical comparisons. Use when analyzing single-base methylation patterns, comparing samples, or preparing data for DMR detection.

bio-workflows-crispr-screen-pipeline

End-to-end CRISPR screen analysis from FASTQ to hit genes. Orchestrates guide counting, QC, statistical analysis with MAGeCK, and hit calling with multiple methods. Use when analyzing pooled CRISPR screens from count data to hit calling.

bio-flow-cytometry-differential-analysis

Differential abundance and state analysis for cytometry data. Compare cell populations between conditions using statistical methods. Use when testing for significant changes in cell frequencies or marker expression between groups.

bio-metabolomics-statistical-analysis

Statistical analysis for metabolomics data. Covers univariate testing, multivariate methods (PCA, PLS-DA), and biomarker discovery. Use when identifying differentially abundant metabolites or building classification models.

bio-metabolomics-normalization-qc

Quality control and normalization for metabolomics data. Covers QC-based correction, batch effect removal, and data transformation methods. Use when correcting technical variation in metabolomics data before statistical analysis.

bio-experimental-design-power-analysis

Calculates statistical power and minimum sample sizes for RNA-seq, ATAC-seq, and other sequencing experiments. Use when planning experiments, determining how many replicates are needed, or assessing whether a study is adequately powered to detect expected effect sizes.

bio-chipseq-differential-binding

Differential binding analysis using DiffBind. Compare ChIP-seq peaks between conditions with statistical rigor. Requires replicate samples. Outputs differentially bound regions with fold changes and p-values. Use when comparing ChIP-seq binding between conditions.

bio-experimental-design-sample-size

Estimates required sample sizes for differential expression, ChIP-seq, methylation, and proteomics studies. Use when budgeting experiments, writing grant proposals, or determining minimum replicates needed to achieve statistical significance for expected effect sizes.

exp-driven-dev

Builds features with A/B testing in mind using Ronny Kohavi's frameworks and Netflix/Airbnb experimentation culture. Use when implementing feature flags, choosing metrics, designing experiments, or building for fast iteration. Focuses on guardrail metrics, statistical significance, and experiment-driven development.

data-analysis

Patterns for data loading, exploration, and statistical analysis

Statistical Hypothesis Testing

Conduct statistical tests including t-tests, chi-square, ANOVA, and p-value analysis for statistical significance, hypothesis validation, and A/B testing

Anomaly Detection

Identify unusual patterns, outliers, and anomalies in data using statistical methods, isolation forests, and autoencoders for fraud detection and quality monitoring

A/B Test Analysis

Design and analyze A/B tests, calculate statistical significance, and determine sample sizes for conversion optimization and experiment validation

data-analysis

Statistical analysis, outlier detection, and data transformation utilities.

A/B Test Validation

Validating A/B test implementations including traffic splitting accuracy, statistical significance calculation, metric tracking, and experiment cleanup.

ab-testingexperimentationstatistical+2

Test Flakiness Detection

Detecting and diagnosing flaky tests using statistical analysis, execution recording, environmental factor isolation, and quarantine strategies.

flakydetectionstatistical+2

CSV Data Summarizer

CSV data analysis skill. Uses Python and pandas to analyze CSV files and generate statistical summaries and quick visualizations. Automatically invoked when a user uploads or mentions a CSV file or requests analysis of tabular data.

csv-data-summarizer

Analyzes CSV files and automatically generates comprehensive summaries with statistical insights, data quality checks, and visualizations using Python and pandas. No questions asked — just upload a CSV and get a full analysis immediately.

mcmc-sampling-stan

Guide for performing Markov Chain Monte Carlo (MCMC) sampling using RStan or PyStan. This skill should be used when implementing Bayesian statistical models, fitting hierarchical models, working with Stan modeling language, or running MCMC diagnostics. Applies to tasks involving posterior sampling, Bayesian inference, and probabilistic programming with Stan.

distribution-search

Guidance for finding probability distributions that satisfy specific statistical constraints such as KL divergence targets, entropy requirements, or moment conditions. This skill should be used when tasks involve constructing discrete or continuous probability distributions with specified divergence measures, entropy values, or other distributional properties through numerical optimization.

adaptive-rejection-sampler

Guidance for implementing adaptive rejection sampling (ARS) algorithms for generating random samples from log-concave probability distributions. This skill should be used when tasks involve implementing ARS, rejection sampling, or Monte Carlo methods that require sampling from custom probability distributions, particularly in R or other statistical computing languages.

feal-differential-cryptanalysis

Guidance for implementing differential cryptanalysis attacks on FEAL and similar Feistel ciphers. This skill should be used when asked to break FEAL encryption, recover cipher keys through differential attacks, or implement cryptanalysis techniques on block ciphers with weak round functions. Covers proper differential characteristic construction, not ad-hoc statistical methods.

data-analysis

Data analysis and statistical computation. Use when user needs "数据分析/统计/计算指标/数据洞察". Supports general analysis, financial data (stocks, returns), business data (sales, users), and scientific research. Uses pandas/numpy/scikit-learn for processing. Automatically activates data-base for data acquisition.

pine-backtester

Implements comprehensive backtesting capabilities for Pine Script indicators and strategies. Use when adding performance metrics, trade analysis, equity curves, win rates, drawdown tracking, or statistical validation. Triggers on "backtest", "performance", "metrics", "win rate", "drawdown", or testing requests.

Data Anomaly Detector for Construction

datadrivenconstruction

Detect anomalies and outliers in construction data: unusual costs, schedule variances, productivity spikes. Statistical and ML-based detection methods.

dspy-simba-optimizer

This skill should be used when the user asks to "optimize with SIMBA", "use Bayesian optimization", "optimize agents with custom feedback", mentions "SIMBA optimizer", "mini-batch optimization", "statistical optimization", "lightweight optimizer", or needs an alternative to MIPROv2/GEPA for programs with rich feedback signals.

oracle-nano

francomascareloai

ORACLE NANO v3.1 - Statistical Validator for NautilusTrader/Apex Trading. Compact skill for context-limited sessions (~3KB). FOCO: WFA, Monte Carlo, PSR/DSR, GO/NO-GO decisions, Apex compliance. DROID: oracle-backtest-commander.md tem conhecimento COMPLETO. APEX: 5% trailing DD ($2.5k on $50k) - MUITO mais rigoroso que FTMO! Triggers: "Oracle", "backtest", "validate", "WFA", "Monte Carlo", "Sharpe", "DSR", "overfitting", "GO/NO-GO", "challenge", "live", "Apex"

mvp-case-builder

Construct statistical arguments for MVP/awards. Narrative framing, comparison to past winners, advanced metrics, counter-arguments.

performance-benchmark-specialist

Performance benchmarking expertise for shell tools, covering benchmark design, statistical analysis (min/max/mean/median/stddev), performance targets (<100ms, >90% hit rate), workspace generation, and comprehensive reporting

Quantitative Analyst

Expert in quantitative finance, algorithmic trading, and financial data analysis using Python (Pandas/NumPy), statistical modeling, and machine learning.

python_data_stack

Statistical modeling toolkit. OLS, GLM, logistic, ARIMA, time series, hypothesis tests, diagnostics, AIC/BIC, for rigorous statistical inference and econometric analysis.

data-scientist

Expert in statistical analysis, predictive modeling, machine learning, and data storytelling to drive business insights.

data-analyst

Expert data analyst specializing in business intelligence, data visualization, and statistical analysis. Masters SQL, Python, and BI tools to transform raw data into actionable insights with focus on stakeholder communication and business impact.

quant-analyst

Expert quantitative analyst specializing in financial modeling, algorithmic trading, and risk analytics. Masters statistical methods, derivatives pricing, and high-frequency trading with focus on mathematical rigor, performance optimization, and profitable strategy development.

data-researcher

Expert data researcher specializing in discovering, collecting, and analyzing diverse data sources. Masters data mining, statistical analysis, and pattern recognition with focus on extracting meaningful insights from complex datasets to support evidence-based decisions.

data-scientist

Expert data scientist specializing in statistical analysis, machine learning, and business insights. Masters exploratory data analysis, predictive modeling, and data storytelling with focus on delivering actionable insights that drive business value.

marketing-cro

Use when optimizing conversion rates, designing A/B tests, or improving landing pages. Covers A/B testing methodology, landing page optimization, form design, statistical significance, funnel analysis, and CRO prioritization frameworks.

quantitative-analysis

You must use this when selecting statistical tests, interpreting effect sizes, or conducting power analysis.

code-data-analysis-scaffolds

Use when beginning technical work that requires a structured approach—writing tests before code (TDD), planning data exploration (EDA), designing statistical analyses, clarifying modeling objectives (causal vs. predictive), or validating results. Invoke when the user mentions "write tests for", "explore this dataset", "analyze", "model", "validate", or when technical work needs systematic scaffolding before execution.