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Data & Analytics
Data analysis, BI, visualization, datasets, statistics, and ML workflows
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Showing 11,569–11,592 of 12,625 skills
- Datarobot Data PreparationTools and guidance for data upload, dataset management, data validation, and preparing data for DataRobot projects. Use when uploading datasets, managing data, or validating data for DataRobot.Votes: 0GitHub stars: 29
- Geo ToolkitParse, convert, geocode, visualize, and measure geographic data. Use for address cleanup, geo file conversion, mapping, and distance workflows.Votes: 0GitHub stars: 99
- Redistricting AnalysisRedistricting analysis in R using the redistverse ecosystem. Use whenever the user is working with redist, redistmetrics, ggredist, geomander, adj, alarmdata, PL94171, censable, easycensus, tinytiger, baf, rict, or redistio. Covers the complete pipeline: Census and spatial data loading, adjacency graph construction, SMC/MCMC simulation, constraints (population balance, county splits, VRA compliance), convergence diagnostics, plan metrics (compactness, partisan fairness, splits), visualization...Votes: 0GitHub stars: 18
- Pdf ExtractorThis skill should be used when the user asks to "extract text from PDF", "convert PDF to text", "parse PDF", "read PDF contents", "extract data from documents", "batch PDF extraction", "PDF to markdown", "OCR PDF", "get text from PDF files", "I have a PDF", "can you read this PDF", "what's in this PDF", "summarize this PDF", "open PDF file", "extract from [filename].pdf", or needs to process PDF documents for data extraction. Handles single-file extraction, batch processing, and OCR for scann...Votes: 0GitHub stars: 12
- Segmentation ExpertIdentify, analyze, and act on customer segments to uncover hidden patterns and understand behavior differences. Use when investigating KPI changes to understand which customers drove them, planning targeted initiatives, building customer personas, or analyzing performance differences across groups. Helps select meaningful segmentation dimensions, create actionable segments, analyze performance differences, calculate segment contributions, and generate segment-specific recommendations.Votes: 0GitHub stars: 28
- Kpi Tree ArchitectBuild comprehensive KPI trees from North Star metrics. Use when users need to decompose metrics into hierarchical driver structures, create MECE (Mutually Exclusive, Collectively Exhaustive) breakdowns, identify leverage points, map performance drivers, or prepare for root cause analysis. Essential for setting up analytical foundations after defining a North Star metric.Votes: 0GitHub stars: 28
- Influential Factors DetectiveIdentify and analyze qualitative factors that influence KPIs but can't be measured as numbers. Use when users need to find non-quantifiable drivers affecting metrics (like copy quality, design aesthetics, timing), plan A/B tests for subjective elements, bridge the gap between data and design/content decisions, understand why quantitative analysis is incomplete, optimize messaging or UX elements, or identify the actual levers to pull for improving KPIs at the leaf nodes of a KPI tree.Votes: 0GitHub stars: 28
- Cohort Analysis SpecialistTrack customer behavior over time by grouping customers based on shared characteristics or experiences. Use when measuring retention rates, understanding how customers evolve over time, comparing new vs old user behavior, evaluating product changes by cohort, identifying at-risk cohorts early, or calculating LTV by cohort. Essential for understanding retention, lifecycle patterns, and how product changes affect different user vintages.Votes: 0GitHub stars: 28
- Analytics OrchestratorIntelligent entry point to the analytics ecosystem based on "The Power of Analytics" book by Florian Bonnet. Guides users to the right analytics agent based on their needs, recommends workflow sequences, and provides clear instructions for launching agents. Use when users need help choosing between analytics agents, want to start an analytics project but aren't sure where to begin, or ask "what can you help me with" in an analytics context. Also use when users mention analytics tasks like def...Votes: 0GitHub stars: 28
- Analysis PlannerStructure analysis investigations before diving into data, preventing wasted time and ensuring thoroughness. Use when users need to plan any significant analysis, investigate KPI changes, respond to stakeholder questions, plan feature/experiment analysis, or when previous analyses were unfocused. Helps define clear goals, generate testable hypotheses, create systematic analysis roadmaps, identify required data, estimate timelines, and prevent analysis paralysis.Votes: 0GitHub stars: 28
- Scientific VisualizationCreate publication figures with matplotlib/seaborn/plotly. Multi-panel layouts, error bars, significance markers, colorblind-safe, export PDF/EPS/TIFF, for journal-ready scientific plots.Votes: 0GitHub stars: 17
- Niche Signal DiscoveryDeprecated alias. This skill was renamed to `deepline-scoring`. Use when a user or script still invokes `/niche-signal-discovery`: immediately load and follow the `deepline-scoring` skill instead. Triggers: ICP analysis, niche signals, won vs lost analysis, differential signals, signal discovery, ICP signal report, account scoring signals, lead scoring, first-party signals, buyer signals.Votes: 0GitHub stars: 63
- Social Performance ReviewMonthly social media performance review for SMBs. Analyses post-level and account-level data from Instagram, LinkedIn, Facebook, or TikTok. Identifies what worked, what didn't, and why. Produces a client-ready report and specific recommendations that feed back into the content calendar. Accepts CSV exports, screenshots, or manual data input.Votes: 0GitHub stars: 202
- Evaluate ModelLoad the latest model checkpoint, run evaluation on the test set, and generate a metrics report with confusion matrix. Use this after training to assess model performance or to re-evaluate a specific checkpoint.Votes: 0GitHub stars: 67
- Synthesize By LobGroups and prioritizes enriched findings by Line of Business (LOB) using the mappings defined in `references/lob-mappings.json`. Produces a structured output organized by LOB with severity-ranked findings.Votes: 0GitHub stars: 4
- Enrich FindingsTakes raw dashboard findings and enriches them with external context via web search. Transforms data-only insights into contextualized intelligence by adding competitor dynamics, market trends, and macro factors.Votes: 0GitHub stars: 4
- Analyze DashboardsBrowses the Strategy Cloud library, inventories all dashboards, opens each one, and detects anomalies, threshold breaches, and trends using the detection patterns defined in `references/finding-patterns.json`.Votes: 0GitHub stars: 4
- Cost TrackingModel-specific pricing tables and cost calculation utilities for Claude API usage tracking and budget management.Votes: 0GitHub stars: 2
- Analysis PatternsReusable analysis patterns and heuristics for plugin execution data. Provides standardized methods for pattern detection, anomaly scoring, and improvement signal extraction.Votes: 0GitHub stars: 2
- Reinforcement LearningReinforcement Learning best practices for Python using modern libraries (Stable-Baselines3, RLlib, Gymnasium). Use when: - Implementing RL algorithms (PPO, SAC, DQN, TD3, A2C) - Creating custom Gymnasium environments - Training, debugging, or evaluating RL agents - Setting up hyperparameter tuning for RL - Deploying RL models to productionVotes: 0GitHub stars: 9
- Deep LearningComprehensive guide for Deep Learning with Keras 3 (Multi-Backend: JAX, TensorFlow, PyTorch). Use when building neural networks, CNNs for computer vision, RNNs/Transformers for NLP, time series forecasting, or generative models (VAEs, GANs). Covers model building (Sequential/Functional/Subclassing APIs), custom training loops, data augmentation, transfer learning, and production best practices.Votes: 0GitHub stars: 9
- HealthUse when the user wants to check dataset quality, diagnose eval issues, or before running evolve. Checks size, difficulty distribution, dead examples, coverage, and splits. Auto-corrects issues found.Votes: 0GitHub stars: 49
- Peec ReportWeekly / monthly closed-loop reporter for Peec AI visibility growth. Measures what moved (visibility per prompt, cluster, zone) against what was invested (content published, pitches sent, forum answers), detects winning patterns, and outputs a ranked next-actions list — not a dashboard. Closes the feedback loop for the growth agent. Use weekly for active projects or monthly for maintenance-mode.Votes: 0GitHub stars: 9
- Peec LearnCross-project pattern layer for the Peec AI growth loop. After any Peec skill completes (or after peec-report closes a cycle), extract 1–3 concrete patterns from the output and persist them to SkillMind via mcp__skillmind__add_pattern / remember. On the next orchestrator run, recall matching patterns and pass them in as priors — so lessons learned on project A inform decisions on project B. Use when a Peec skill has produced an artifact (brief, zone map, outreach log, decision, learnings.json...Votes: 0GitHub stars: 9