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Found 1,573 Skills
This skill should be used when the user asks to "audit for AI visibility", "optimize for ChatGPT", "check GEO readiness", "analyze hedge density", "generate agentfacts", "check if my site works with AI search", "test LLM crawlability", "check discovery gap", or mentions Generative Engine Optimization, AI crawlers, Perplexity discoverability, or NANDA protocol.
Create publication-quality plots and visualizations using matplotlib and seaborn. Works with ANY LLM provider (GPT, Gemini, Claude, etc.).
Build MCP servers with TypeScript on Cloudflare Workers. Covers tools, resources, prompts, tasks, authentication (API keys, OAuth, Zero Trust), and Cloudflare service integrations. Prevents 20 documented errors. Use when exposing APIs to LLMs or troubleshooting export syntax errors, transport leaks, server instance reuse bugs, CORS misconfigurations, or task validation errors.
Build stateless MCP servers with TypeScript on Cloudflare Workers using @modelcontextprotocol/sdk. Provides patterns for tools, resources, prompts, and authentication (API keys, OAuth, Zero Trust). Use when exposing APIs to LLMs, integrating Cloudflare services (D1, KV, R2, Vectorize), or troubleshooting export syntax errors, unclosed transport leaks, or CORS misconfigurations.
Use when running tests to validate implementations, collecting test evidence, or debugging failures. Load in TEST state. Covers unit tests (pytest/jest), API tests (curl), browser tests (Claude-in-Chrome), database verification. All results are code-verified, not LLM-judged.
Convert documents to Markdown using markitdown. Use when you need to extract text and convert PDF, Word, PowerPoint, Excel, HTML, CSV, JSON, XML, images (with EXIF/OCR), audio, ZIP archives, YouTube URLs, or EPUBs to Markdown format for LLM processing or text analysis.
Battle-tested PyTorch training recipes for all domains — LLMs, vision, diffusion, medical imaging, protein/drug discovery, spatial omics, genomics. Covers training loops, optimizer selection (AdamW, Muon), LR scheduling, mixed precision, debugging, and systematic experimentation. Use when training or fine-tuning neural networks, debugging loss spikes or OOM, choosing architectures, or optimizing GPU throughput.
Calculate the full Amazon FBA fee stack and the true net profit and margin for a product, and compare FBA versus FBM on cost. Walks the referral fee, the FBA fulfillment fee by size tier and weight, dimensional weight, monthly and Q4 storage, long-term storage risk, inbound shipping, removal fees, and the optional cost lines, then returns net profit, net margin, and break-even ACoS. Use when a user asks to calculate FBA fees, profit per unit, net margin, break-even, whether a product is profitable, fulfillment cost, shipping cost, dimensional weight, storage fees, inbound shipping, removal fees, or to compare FBA versus FBM. Trigger phrases. "FBA calculator", "FBA fees", "profit per unit", "net margin", "break-even", "is this profitable", "shipping calculator", "fulfillment cost", "FBA vs FBM", "dimensional weight", "storage fees", "inbound shipping", "removal fees". Works with zero tools. the user provides price, cost, dimensions, weight, and rates.
Defend Amazon chargebacks and A-to-z claims within the 3-day A-to-z response window. Identifies the claim type, builds the evidence packet (tracking, signature, messaging history, fulfillment proof), and writes the response narrative Amazon's case reviewers read for. Use when a user asks about chargebacks, A-to-z claims, INR (item not received), SNAD (significantly not as described), payment disputes, or defending an order claim. Trigger phrases: "chargeback", "A-to-z claim", "INR", "SNAD", "dispute", "buyer claim", "order defense". Works with zero tools. the user pastes the claim text and order data.
Diagnose why a listing is losing the Amazon Buy Box (Featured Offer) and build a plan to win it back. Covers seller-health signals, pricing relative to the competing offer, fulfillment method, stock, and account metrics. Use when a user asks why they lost the Buy Box, how to win the Featured Offer, why a reseller is beating them, or why their own listing shows another seller's offer. Trigger phrases: "buy box", "featured offer", "lost the buy box", "win the buy box", "buy box percentage", "another seller has my listing". Works with zero tools. the user describes the offer and account state.
Forecast cash flow under Amazon's DD+7 (Delivery-Date-Based Reserve) payout policy. Models when funds clear, sizes the working-capital buffer the seller needs, and stress-tests scenarios for slow shipping or refund spikes. Use when a user asks about DD+7, Delivery-Date-Based Reserve, payout delays, working capital, cash flow under the new reserve policy, or how much cash they need to keep on hand. Trigger phrases: "DD+7", "payout reserve", "delivery date reserve", "working capital", "cash flow", "Amazon holds my money". Works with zero tools. the user provides sales velocity, fulfillment mix, and seasonality.
Audit Amazon Payments report for fee errors. Finds incorrect FBA fulfillment fees (wrong size tier), missing referral fee credits on refunds, duplicate charges, and FBA storage discrepancies, and produces an FBA fee-discrepancy case packet per finding. Use when a user asks about Amazon fee errors, overcharged fees, wrong size tier, missing referral refunds, fee audit, or Payments report analysis. Trigger phrases: "fee audit", "overcharged", "wrong fee", "size tier error", "referral fee refund", "payments report", "FBA fee dispute". Works with zero tools. the user pastes Payments report rows.