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Found 178 Skills
Statistics, probability, linear algebra, and mathematical foundations for data science
Verify statistics from raw data with methodology checking, significance testing, claim validation, and bias detection. Use when fact-checking statistical claims, validating research findings, or auditing data analysis.
Leverage the market statistics capability of SellerSprite to output a market statistics dashboard by category node, including metrics such as average rating, average price, BSR, sales volume, number of sellers, and new product-related indicators for top Listings. It is suitable for quickly judging the market quality and competitive landscape of a certain category. This skill is triggered when the user mentions category market statistics, market selection dashboard, market foundation assessment, node market quality, top product statistics, SellerSprite market statistics, or category statistics. Even if the user does not explicitly mention "SellerSprite", this skill should be triggered as long as the requirement is to view aggregated statistical results by category node.
Apply statistical methods to financial data including descriptive statistics, covariance estimation, regression, hypothesis testing, and resampling. Use when the user asks about return distributions, correlation between assets, building a covariance matrix, running a CAPM regression, testing whether alpha is significant, checking if returns are normal, or estimating confidence intervals. Also trigger when users mention 'volatility', 'how correlated are these', 'fat tails', 'skewness', 'R-squared', 'beta of a fund', 'bootstrap a Sharpe ratio', 'shrinkage estimator', 'Ledoit-Wolf', or ask why their optimizer produces unstable weights.
Audits optimizer table statistics for staleness, missing coverage, and data quality issues using SHOW STATISTICS. Use when diagnosing poor query performance, unexpected plan changes, or after bulk data changes to identify stale statistics requiring refresh via CREATE STATISTICS.
10 statistical analysis skills. Trigger: statistical tests, Bayesian analysis, hypothesis testing, sampling. Design: method guides covering assumptions, code, and result interpretation.
WeRead Assistant — Search books, manage bookshelf, view notes and underlines, browse book reviews, reading statistics, discover and recommend good books
Analyzes code statistics by language for project insight, CI/CD metrics, or before refactoring. Use this skill when understanding project composition, measuring change impact, or generating CI/CD metrics
Analyze files and get detailed metadata including size, line counts, modification times, and content statistics. Use when users request file information, statistics, or analysis without modifying files.
Fetch project statistics from SpecStory Cloud. Run when user says "get project stats", "show SpecStory stats", "project statistics", "how many sessions", or "SpecStory metrics".
This skill should be used when users want to generate comprehensive statistics and overview of their Obsidian vault, including file counts, types, tags, links, folder structure, and other metadata analysis.
Fetches aggregated trace metrics (token usage, latency, trace counts, quality evaluations) from MLflow tracking servers. Triggers on requests to show metrics, analyze token usage, view LLM costs, check usage trends, or query trace statistics.