checkout-analysis

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 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.

An instant, at-a-glance read on your store's health from the last 24 hours — with the option to save it as a live Cowork dashboard artifact or schedule a recurring report. Use to check on how the overall store is doing, save a live dashboard, or schedule a recurring summary.

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.

Run NV-Reason-CT inference on user-provided 3D NIfTI chest or abdominal CT volumes for engineering and research workflows. Not for diagnosis, treatment, or clinical reporting.

NVIDIA CDF curation and retrieval. Cosmos Curator video and image pipelines (split, dedup, shard, annotate) with filtering, captioning, and embedding. Cosmos Dataset Search ingest, search, and capability qualification. TAO data mining embeddings and neighbor matching. Ships domain event catalogs, including workplace employee conduct monitoring, which requires legal review before use. Use when a request names Cosmos Curator, Cosmos Dataset Search, CDF, or their Make and CLI surfaces. Not for model training, orchestration, or unrelated dataset questions.

Use when a task needs to search or add documents through NeMo Retriever MCP.

Brev instance operating guidance for NeMo-RL agents working in /home/ubuntu/RL with limited workspace disk, a larger /ephemeral volume, and optional /home/ubuntu/RL/.env secrets. Use when running nemo-rl-auto-research campaigns, experiments, training jobs, model or dataset downloads, shared cache-heavy commands, log-producing runs, checkpoint generation, W&B or Hugging Face authenticated workflows, or any workflow that may create large files on Brev.

Performs deep Root Cause Analysis (RCA) on NVIDIA TAO Visual ChangeNet classification experiments with image-evidence-driven investigation. Use when analyzing ChangeNet model failures, investigating poor recall / FAR / PASS-NO_PASS metrics, auditing visual inspection pipeline quality, or running an RCA report for an AOI defect-detection model. Trigger phrases include "RCA on my ChangeNet model", "why is my AOI model failing", "audit ChangeNet predictions", "investigate FAR regressions", "root cause analysis on visual-changenet".

Run TAO Data Services object-detection gap analysis from ground-truth and inference annotations. Use when an object detection workflow needs to identify weak images by comparing model predictions against ground truth using per-class recall, precision, and AP50 thresholds. Use when the user asks to "analyze OD gaps", "find weak OD images", or "run mAP gap analysis".

Look up and read Hugging Face paper pages in markdown, and use the papers API for structured metadata such as authors, linked models/datasets/spaces, Github repo and project page. Use when the user shares a Hugging Face paper page URL, an arXiv URL or ID, or asks to summarize, explain, or analyze an AI research paper.

Generate a reproducible final report, literature-outcome synthesis, JSON summary, and refreshed progress plot for a stopped or interrupted NVFLARE Auto-FL campaign.