stockout-prevention

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.

Diagnoses why a seller's listing isn't found in search and helps make it more discoverable. Checks whether the listing is discoverable at all, then optimizes the content shoppers search on — title, description, bullet points, and generic keywords — with the seller's approval. Triggers on: not showing up in search, can't be found, not discoverable, improve ranking, search visibility, optimize my listing, SEO. Do NOT use for: not-buyable (use listing-buyability) or fixing reported issues (use listing-issues).

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.

Rigor Explore compatible skill slug for meaningful and potentially novel deep learning research candidates. Use when the researcher has chosen the task family, dataset, benchmark, evaluation method, provided SOTA references, and wants candidate-only exploration on top of `current_research` with auditable repo understanding, idea gating, fair comparison, and governed experiments written to `explore_outputs/`. Do not use for README-first trusted reproduction, open-ended direction finding, narrow code-only or run-only exploration, passive repo analysis, verified novelty claims, or implicit experimentation.

Rigor Reproduce compatible skill slug for README-first deep learning repository reproduction. Use when the user wants an end-to-end, minimal-trustworthy flow that reads the repository first, selects the smallest documented inference or evaluation target, coordinates intake, setup, trusted execution, optional trusted training, optional repository analysis, and optional paper-gap resolution, enforces conservative patch rules, records evidence assumptions deviations and human decision points, and writes the standardized `repro_outputs/` bundle. Do not use for paper summary, generic environment setup, isolated repo scanning, standalone command execution, silent protocol changes, score chasing, or broad research assistance outside repository-grounded reproduction.

Rigor Train skill for deep learning research repositories. Use when a documented or selected training command should be run conservatively for startup verification, short-run verification, full kickoff, or resume, with command, config, seed, log, checkpoint, status, and metric evidence written to standardized `train_outputs/`. Do not use for environment setup, exploratory sweeps, speculative idea implementation, or end-to-end orchestration.

Rigor Improve / Rigor Explore run leaf skill for bounded exploratory evidence in deep learning research repositories. Use when the researcher explicitly authorizes exploratory runs such as small-subset validation, short-cycle guess-and-check, batch sweeps, idle-GPU search, or quick transfer-learning trials, with fair-comparison caveats and no-overclaim summaries in `explore_outputs/`. Do not use for end-to-end exploration orchestration on top of `current_research`, trusted baseline execution, conservative training verification, default routing, verified SOTA claims, or implicit experimentation.

Search, scrape, crawl, extract structured data, and monitor web pages via the ScrapeGraph AI CLI. Use when the user asks to search the web, scrape a webpage, grab content from a URL, extract JSON from a site, crawl documentation or site sections, monitor a page for changes, inspect request history, check ScrapeGraph credits, or validate API setup.

When the user wants to create sales collateral, pitch decks, one-pagers, objection handling docs, or demo scripts. Also use when the user mentions 'sales deck,' 'pitch deck,' 'one-pager,' 'leave-behind,' 'objection handling,' 'deal-specific ROI analysis,' 'demo script,' 'talk track,' 'sales playbook,' 'proposal template,' 'buyer persona card,' 'battle card,' 'battlecard,' 'competitive one-pager,' 'win-loss analysis,' 'why are we losing deals,' 'loss reasons,' 'how do I respond to this objection,' 'prospect just said,' 'help my sales team,' 'sales materials,' or 'what should I give my sales reps,' 'cold call script,' or 'voicemail script.' Use this for any document or asset that helps a sales team close deals. For public competitor comparison pages, see competitors. For running buyer interviews or churn research, see customer-research. For marketing website copy, see copywriting. For cold outreach emails, see cold-email. For the offer being sold (bonuses, guarantees, pricing structure), see offers.

Web search and content extraction with Tavily and Exa via inference.sh CLI. Apps: Tavily Search, Tavily Extract, Exa Search, Exa Answer, Exa Extract. Capabilities: AI-powered search, content extraction, direct answers, research. Use for: research, RAG pipelines, fact-checking, content aggregation, agents. Triggers: web search, tavily, exa, search api, content extraction, research, internet search, ai search, search assistant, web scraping, rag, perplexity alternative

When the user wants to conduct, analyze, or synthesize customer research. Use when the user mentions "customer research," "ICP research," "talk to customers," "analyze transcripts," "customer interviews," "survey analysis," "support ticket analysis," "voice of customer," "VOC," "build personas," "customer personas," "jobs to be done," "JTBD," "what do customers say," "what are customers struggling with," "Reddit mining," "G2 reviews," "review mining," "digital watering holes," "community research," "forum research," "competitor reviews," "customer sentiment," "PMF survey," "product/market fit survey," "customer interview questions," "interview outreach," "Sales Safari," or "find out why customers churn/convert/buy." Use for analyzing existing research assets, mining online sources, AND running primary research (interviews and surveys). For writing copy informed by research, see copywriting. For acting on research to improve pages, see cro.