Data Analysis

social-graph-ranker is the weighted graph-ranking layer for warm intro discovery, bridge scoring, and network gap analysis across X and LinkedIn. Use the social-graph-ranker skill when you need a reusable ranking engine for Lead Research, not a full outbound or network-maintenance workflow.

regex-vs-llm-structured-text skill for choosing regex or LLM in structured text extraction. Start with deterministic parsing, add LLM validation for low-confidence edge cases, and use a cheaper, more reliable pipeline for documents, forms, invoices, and data analysis.

clickhouse-io is a ClickHouse-focused skill for schema design, analytical SQL, ingestion patterns, and performance tuning. Use it to guide MergeTree choices, partitioning, materialized views, and workload-specific query optimization.

data-analyst is a minimal GitHub skill that guides agents toward SQL, pandas, and basic statistical analysis for data exploration. Best for users who want code-backed queries, transformations, and interpretations from a single SKILL.md prompt layer.

retro is a project retrospective skill for engineering teams. It analyzes commit history, work patterns, and prior learnings to generate a structured weekly retro with continuity. Use retro for sprint reviews, what did we ship questions, and Project Management check-ins.

startup-metrics-framework helps founders, analysts, and operators calculate startup KPIs like CAC, LTV, burn multiple, runway, and growth metrics for SaaS, marketplace, consumer, and B2B startups.

Use the market-sizing-analysis skill to build structured TAM, SAM, and SOM estimates with top-down, bottom-up, and value-theory methods. Covers install context, key files, inputs, workflow, and practical usage for startup market sizing and Data Analysis.

startup-financial-modeling helps agents build 3-5 year startup finance models with cohort revenue, cost structure, burn, runway, and fundraising scenarios. Best for founders and finance leads who need install context, clear inputs, and practical usage guidance from the skill's SKILL.md.

risk-metrics-calculation helps compute portfolio risk metrics like VaR, CVaR, Sharpe, Sortino, beta, volatility, and drawdown. Use it to turn return series into structured risk reporting, Python implementation patterns, and practical interpretation for finance workflows.

The backtesting-frameworks skill helps design and review trading strategy backtests with stronger controls for look-ahead bias, survivorship bias, overfitting, transaction costs, and walk-forward validation in Finance.

spark-optimization is a practical guide to diagnosing slow Apache Spark jobs with partitioning, shuffle, skew, caching, and memory tuning. Use it to install the skill from wshobson/agents, read SKILL.md, and apply evidence-based fixes from Spark UI symptoms, cluster settings, and query patterns.

The user-personas skill creates 3 refined personas from research data with JTBD, pains, gains, and unexpected insights. Use it for user-personas for UX Research, segmentation, onboarding strategy, and product decisions when you have surveys, interviews, or other source material.

market-sizing helps estimate TAM, SAM, and SOM with top-down and bottom-up methods. Use it for Market Research workflows, market entry decisions, investor decks, and launch planning when you need a defensible logic trail, assumptions to validate, and a practical first-pass market estimate.

summarize-interview turns a customer interview transcript into a structured discovery summary with JTBD, current solution, satisfaction signals, key insights, and action items. Use it for interview recordings, transcript cleanup, and concise summaries for product teams, researchers, founders, or Data Analysis workflows.

user-segmentation helps turn feedback, interviews, tickets, surveys, and usage logs into distinct behavior-based user segments. Built for Data Analysis, it identifies at least 3 actionable groups using jobs-to-be-done, motivations, and unmet needs rather than demographics alone.

The sentiment-analysis skill turns user feedback into segment-level insights, sentiment scores, JTBD, and product impact. Use it for sentiment-analysis for Data Analysis on reviews, surveys, support notes, or social listening when you need a practical sentiment-analysis guide, not a generic polarity check.

The sql-queries skill turns business questions and rough analytics goals into optimized SQL for BigQuery, PostgreSQL, MySQL, and other dialects. It reads schema context, clarifies filters and aggregations, and helps with sql-queries for Data Analysis, reporting, and exploration.

Perform cohort-analysis on user retention, engagement decay, and feature adoption by cohort. This cohort-analysis skill is built for Data Analysis workflows that need validation, calculation, visualization, and clear insights from structured user behavior data.

ab-test-analysis helps you evaluate A/B test results with statistical rigor, including sample size validation, confidence intervals, significance testing, and ship/extend/stop recommendations. Use it for experiment review, split-test interpretation, and decision-making for Data Analysis workflows.

huggingface-vision-trainer helps you install and use a Hugging Face skill for vision training jobs: object detection, image classification, and SAM/SAM2 segmentation. It covers dataset prep, cloud GPU setup, evaluation, Trackio logging, and pushing results to the Hub. Ideal for backend automation and repeatable training workflows.

huggingface-trackio helps track ML training runs with Trackio. Use this skill to log metrics from Python, add training alerts, and retrieve or analyze runs with the trackio CLI. It supports real-time dashboards, Hugging Face Space sync, and JSON output for automation, making huggingface-trackio useful for experiment tracking and data analysis.

The huggingface-best skill helps you find the best model for a task by checking Hugging Face benchmark leaderboards and filtering by device limits and model size. Use it for model recommendations in coding, reasoning, chat, OCR, RAG, speech, vision, or multimodal work when you need a practical shortlist, not a generic model list.

hv-analysis is a horizontal-vertical research skill for turning a product, company, concept, technology, or person into a structured analysis report. Use the hv-analysis skill for deep research, competitive comparison, and report-ready output, especially when you need hv-analysis for Data Analysis or a polished PDF workflow.

Workspace Data Analyst is a lightweight skill for data analysis in your workspace. It analyzes CSV files, checks headers, summarizes totals, averages, and outliers, and provides concise next-step insights. The Workspace Data Analyst skill is ideal for quick file-aware reviews before deeper modeling.