store-pulse

Find, build and launch A/B tests on a Noibu-monitored store: ranked test ideas from 30 days of Noibu data and the live site, flag-gated variation code, a pull request or Shopify preview theme, automated QA, and a started test. Use for "what should we A/B test", CRO or experiment ideas, building a specific test, implementing a test already found, or taking a Noibu draft test live. Requires the Noibu MCP connector.

Audit a website for WCAG 2.1 AA accessibility violations using automated scanning and Noibu traffic data, and optionally draft the fixes. Use when you want to know what's inaccessible across the store, check WCAG or ADA compliance, find contrast or heading errors, audit for screen reader support, generate an accessibility report, or fix accessibility violations with pull requests or tickets.

Builds a rich business-context Markdown file (a CLAUDE.md / context.md) so Noibu skills and Claude stop hallucinating and reason with real context about the business. Use this skill whenever someone wants to create, set up, or improve their business context file, onboard a new store to Noibu, 'build my MD file', 'make a context file', 'set up my CLAUDE.md', capture company background for the AI, or asks why Claude keeps getting their business wrong. Also trigger on looser phrasings like 'help Claude understand my business', 'document my store for the AI', 'what should I tell Claude about my company', or when a user is starting with Noibu and has no context file yet. Even if the user just says 'build the MD file' or 'set up context', use this skill. It does deep web research on the business (always via a subagent), interviews the user about goals, money leaks, deployment process, and team setup, writes a clean Markdown file, then persists the context to the Noibu backend for the domain.

Analyze checkout performance and health using Noibu data. Use when you want to know where shoppers drop off in the checkout funnel, what payment or delivery methods customers are using, why completion rates are low, what priority errors are hurting checkout, or how cart and order values benchmark.

Analyze product and collection performance using Noibu data. Use when you want to know which products are underperforming, what your best-selling product type is, why a product isn't converting, how your collections are performing, which products get views but no sales, or where shoppers drop off in the product funnel.

  Required reference for calling `noibu_*` tools — field and measure semantics,   query constraints (the `orderBy` requirement, row caps,   unique-measure rule), the call-metadata argument convention (`rationale`, `skill`), and domain   resolution. Also covers parsing of pasted `console.noibu.com` URLs.   Loads alongside topical Noibu skills   (e.g., `checkout-analysis`, `tech-diagnosis`), not instead of them — they   own routing for their respective domains.

Analyze segment and traffic performance using Noibu data. Use when you want to know which channels, devices, or countries convert best, how mobile compares to desktop, where your traffic is coming from, which segments are underperforming, or where to find your best and worst converting customer segments.

Diagnose technical issues and Core Web Vital performance problems using Noibu data, and recommend a fix. Use when you want to know what's broken across the store, why an error is happening, what's causing errors, the root cause of poor page performance, how to fix a technical issue, why an error rate spiked, or where errors are concentrated.

About 450 ready-made HyperFrames blocks and components installed as editable source - transitions, overlays, titles, kinetic type, captions, charts, map overlays, 3D, camera moves. Use it before hand-building any named visual (CRT scanlines, glitch, film grain, a chart); also for hyperframes add and catalog.

Diagnose and fix common FiftyOne issues automatically. Use when a dataset disappeared, the App won't open, changes aren't saving, MongoDB errors occur, video codecs fail, notebook connectivity breaks, operators are missing, or any recurring FiftyOne pain point needs solving.

Generate a Data Lens connector from an external database schema. Use when users want to connect an external data source (PostgreSQL, BigQuery, Databricks, MySQL, etc.) to FiftyOne Data Lens, or when they have a database schema and want to browse/import that data through the FiftyOne App.

Visualizes datasets in 2D using embeddings with UMAP or t-SNE dimensionality reduction. Use when exploring dataset structure, finding clusters, identifying outliers, or understanding data distribution.

Imports datasets into FiftyOne with automatic format detection. Supports all media types (images, videos, point clouds, MCAP multimodal recordings), label formats (COCO, YOLO, VOC, KITTI), multimodal grouped datasets, LeRobot v3 robot-learning episode datasets, and Hugging Face Hub datasets. Use when importing datasets from local files or Hugging Face, loading autonomous driving data, importing robotics/AV sensor logs (MCAP, ROS bag), importing LeRobot robot-learning episodes (teleop recordings, observation.state/action data), or creating grouped datasets.

Exports FiftyOne datasets to standard formats (COCO, YOLO, VOC, CVAT, CSV, etc.) and Hugging Face Hub. Use when converting datasets, exporting for training, creating archives, sharing data in specific formats, or publishing datasets to Hugging Face.

Creates Jupyter notebooks for FiftyOne workflows including getting-started guides, tutorials, recipes, and full ML pipelines. Use when creating notebooks, writing tutorials, building demos, or generating FiftyOne walkthroughs covering data loading, exploration, inference, evaluation, and export.

Answer finance and market-data questions with the You.com `you-finance` MCP tool: stock prices, tickers, earnings, company financials, and market trends, with payment-aware fallbacks for keyless hosts.