listing-searchability

Guides a seller end-to-end through sending inventory to Amazon's fulfillment network: creating an inbound plan, packing, placement, transportation, delivery windows, and shipment confirmation — plus status checks, modifications, and cancellation. Drives the sequential CREATE→PACK→PLACE→TRANSPORT→DELIVER→SHIP pipeline, polls async operations to completion, and pauses at every decision gate for the seller's choice. Triggers on: send inventory to Amazon, create inbound plan, ship to FBA, inbound shipment status, cancel inbound plan, add tracking, FNSKU labels, prep requirements, schedule FC drop-off. Do NOT use for: stockout / replenishment forecasting (use stockout-prevention), listing issues, advertising, or orders.

Closes and reconciles a seller's completed Amazon month: it retrieves the monthly activity, the settlements overlapping the month, the balances carried across month boundaries, and the payout statuses, then walks the seller through an Amazon-activity reconciliation, a payout receipt check (seller supplies bank deposits — there is no bank integration), and an accountant-ready summary. Read-and-explain only: it posts no entries, changes no accounting records, and never files, submits, pays, or moves money. Triggers on: close the books for last month, help me close January/last month, month-end close, reconcile last month, do my Amazon numbers reconcile, have I received all my payouts, give me my month-end summary for my accountant. Do NOT use for: filing/submitting taxes/VAT/GST or any regulated report, paying or moving money, changing prices/listings/inventory, accessing the seller's bank account, or the current in-progress month.

Helps the account owner, an administrator, or a permissions manager of a Seller Central account invite their secondary users to use the Selling Partner plugin. Runs right after the Amazon Selling Partner Connector connector is connected: it confirms the person can grant agent access, asks whether they want to invite secondary users, then walks them through Manage Your Permissions -> Manage Agents, where they enable the agent for the account and choose which secondary users may authorize it. When the skill runs in Amazon Quick, it adds one extra step — inviting that user as a collaborator in the Quick account. Triggers on: invite users, add a secondary user, manage agents, grant agent access, "let my team use the plugin", onboard my team, give access to another user. Do NOT use for: setting up your own account/marketplace (established by the connect flow), taking selling actions, or User Permissions unrelated to AI agents.

Diagnoses why a seller's listing isn't buyable and relays the specific reason plus the next step. Checks the three things that make a listing buyable — a complete product, a valid purchasable offer, and available inventory — then fixes the offer (preview → approve) or routes inventory elsewhere. Triggers on: not buyable, can't be purchased, "why can't customers buy this", no buy box, listing inactive, missing price / offer. Do NOT use for: search/discoverability (use listing-searchability), fixing reported listing issues (use listing-issues), or inventory replenishment (use stockout-prevention).

Pre-flight compliance gate before any listing write. Identifies which Amazon listing and regulatory requirements (FDA, EPA, CPSC, FCC, FTC, disclosures, GTIN, category gating) apply, asks the seller once for the facts only they know, checks account-side gating, and holds the write until the seller gives an explicit go. Triggers on: "can I list this", "what do I need to sell X", "is this compliant", listing requirements, help me list, or when a sibling listing skill is about to change product claims, ingredients, category, condition, images, or identifiers. Do NOT use for: reported issues (listing-issues), buyability (listing-buyability), search optimization (listing-searchability), or general program-policy Q&A unrelated to listings.

Fixes listing problems that surface as reported issues on a listing — missing or invalid attributes, and suppressions tied to an issue. Reads the listing's issues (severity + enforcement), prioritizes by impact, and previews every fix before it goes live. Triggers on: listing issues, listing errors, fix my listing, attribute errors, suppressed because of an issue, "what's wrong with this listing". Do NOT use for: why a listing isn't buyable when there's no issue (use listing-buyability), search visibility / optimization (use listing-searchability), creating new listings, inventory / stockout, advertising, or orders.

Top-level entry point for any "something's wrong with my listing" question. Does a quick scan to read the listing's status and issues, identifies the symptom, and routes the seller to the right specialist skill — issue-fixing, buyability, searchability, or compliance. Triggers on: something's wrong with my listing, troubleshoot my listing, my product has a problem, listing not working, where do I start, "can I list this", "what do I need to sell X". Routes to: listing-issues, listing-buyability, listing-searchability, listing-compliance.

Answers a seller's business-performance questions — inventory health, traffic, and sales — by querying the Amazon Selling Partner Connector analytics tools. Always discovers the real metric IDs first (never guesses metric names), then retrieves the data with the correct filters, grouping, and time range, and explains the result in plain language. Read-only: it reports numbers, it never changes anything. Triggers on: "how are my sales / sessions / traffic", "am I at risk of a stockout", "how much inventory do I have", "what's my days of supply", "show me page views by ASIN", "when should I restock", "seller analytics", "business report". Do NOT use for: changing prices or listings, creating shipments, tax/GST/financial-settlement reports, or establishing which account/marketplace to use (established by the connect flow).

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".

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.

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.

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

Performs gap analysis on NVIDIA TAO VCN Classify (Visual Component Net) experiments by invoking the pinned TAO data-services container directly via `docker run … gap_analysis vcn_aoi …` — picks the optimal decision threshold, ranks per-sample weakness, and emits a top-K weakest parquet expanded per-lighting for downstream augmentation. Use when analyzing VCN classification failures, picking SDA augmentation targets, or auditing PASS/NO_PASS boundary cases.

Extract false-positive and false-negative gaps from VLM binary-classification-question (BCQ, yes/no) predictions. Use when the user asks to "analyze VLM BCQ gaps", "extract VLM false positives and false negatives", or identify failure cases from a predictions JSON for DEFT root-cause analysis on a binary-classification VLM workflow.

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

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".