AI model or service
Model Context Protocol agent skills, page 106
Model Context Protocol skills, ranked
Ranked by score. Sort bymost stars,trending,newest,recently updated
| # | Skill | Repository | Stars | Used in | Tokens | Auto-check | Licence | Updated |
|---|---|---|---|---|---|---|---|---|
| 5041 | Design a scalable Amazon long-tail keyword portfolio with evidence-based query generation, clustering versus single-keyword isolation, portfolio budget caps, automation drafts, sample safeguards… | xjli360/ | 247 | — | ~524 | Automated safety check: Pass | MIT | 11 days ago |
| 5042 | Diagnose and design low-bid Amazon Ads discovery experiments that probe residual traffic, minimum viable bids, placements, and harvestable search terms under a portfolio cap. | xjli360/ | 247 | — | ~577 | Automated safety check: Pass | MIT | 11 days ago |
| 5043 | Evaluate and improve low-price, high-CPC Amazon products using break-even economics, legitimate bundles or multipacks, long-tail traffic, low-bid discovery, creator channels, and original video ads. | xjli360/ | 247 | — | ~529 | Automated safety check: Pass | MIT | 11 days ago |
| 5044 | Triage negative Amazon reviews into policy violations, suspected abuse, and genuine product feedback, then prepare factual official reports and product-remediation actions. | xjli360/ | 247 | — | ~515 | Automated safety check: Pass | MIT | 11 days ago |
| 5045 | Recover an underperforming Amazon new-product advertising program by diagnosing traffic concentration, sample sufficiency, placement mix, retail readiness, and unit economics in a fixed order. | xjli360/ | 247 | — | ~518 | Automated safety check: Pass | MIT | 11 days ago |
| 5046 | Diagnose why an Amazon new product cannot gain traction by separating retail-readiness, traffic relevance, click-through, conversion, economics, and feedback quality. | xjli360/ | 247 | — | ~524 | Automated safety check: Pass | MIT | 11 days ago |
| 5047 | Create a quantified Amazon new-product launch plan by translating a sales target into comparable-product benchmarks, keyword economics, budget scenarios, milestones, and stop-loss rules. | xjli360/ | 247 | — | ~548 | Automated safety check: Pass | MIT | 11 days ago |
| 5048 | Build an evidence-based Amazon new-product traffic plan that moves from controlled discovery to stable converting terms and measures organic-rank and organic-order changes without claiming causality. | xjli360/ | 247 | — | ~565 | Automated safety check: Pass | MIT | 11 days ago |
| 5049 | Diagnose why an Amazon keyword converts poorly at top of search but better elsewhere by analyzing placement reports, effective bids, competitor context, and controlled experiments. | xjli360/ | 247 | — | ~509 | Automated safety check: Pass | MIT | 11 days ago |
| 5050 | Reduce avoidable Amazon returns through root-cause analysis, accurate listing content, packaging and quality fixes, official Product Support features, manuals, support videos, spare-parts workflows… | xjli360/ | 247 | — | ~531 | Automated safety check: Pass | MIT | 11 days ago |
| 5051 | Audit suspicious Amazon review patterns and proposed review-growth tactics for policy risk, then replace unsafe ideas with official reporting and compliant review programs. | xjli360/ | 247 | — | ~535 | Automated safety check: Pass | MIT | 11 days ago |
| 5052 | Assess whether a team should enter or expand on Amazon using unit economics, cash runway, product-market fit, operational capability, compliance, and staged validation. | xjli360/ | 247 | — | ~533 | Automated safety check: Pass | MIT | 11 days ago |
| 5053 | Design Amazon Ads for legitimate parent-child variations by selecting a hero child, allocating queries by variant attributes, isolating budgets, and monitoring halo effects and inventory. | xjli360/ | 247 | — | ~528 | Automated safety check: Pass | MIT | 11 days ago |
| 5054 | Plan an ad-intensive but policy-compliant Amazon launch that expands indexed and converting keyword coverage while preserving profitability and inventory guardrails. | xjli360/ | 247 | — | ~531 | Automated safety check: Pass | MIT | 11 days ago |
| 5055 | Design Amazon ad architecture around product searchability, query intent, ASIN substitutability, placements, and evidence quality while separating architecture from conversion root causes. | xjli360/ | 247 | — | ~566 | Automated safety check: Pass | MIT | 11 days ago |
| 5056 | Diagnose Amazon ad conversion that declines, stays weak, or fluctuates by separating placement expansion, price-value fit, query relevance, product-page differentiation, and market events. | xjli360/ | 247 | — | ~578 | Automated safety check: Pass | MIT | 11 days ago |
| 5057 | Optimize Amazon ads in an attribution-safe order: placement allocation first, irrelevant-query controls second, and target-level bid changes last. | xjli360/ | 247 | — | ~541 | Automated safety check: Pass | MIT | 11 days ago |
| 5058 | Route an Amazon product into precise-attribute, broad-intent, or no-clear-keyword advertising structures based on product truth, search behavior, conversion, and unit economics. | xjli360/ | 247 | — | ~553 | Automated safety check: Pass | MIT | 11 days ago |
| 5059 | Create evidence-backed Amazon image and A+ briefs with AI while preserving the real product's shape, color, scale, included components, and policy compliance. | xjli360/ | 247 | — | ~551 | Automated safety check: Pass | MIT | 11 days ago |
| 5060 | Turn verified product facts and third-party keyword exports into an auditable AI workflow for filtering queries, selecting ad candidates, drafting listing fields, and preserving evidence for every… | xjli360/ | 247 | — | ~573 | Automated safety check: Pass | MIT | 11 days ago |
| 5061 | Validate whether an apparent Amazon blue-ocean opportunity is driven by durable differentiated demand or by price, promotion, review, variation, or off-platform distortions. | xjli360/ | 247 | — | ~546 | Automated safety check: Pass | MIT | 11 days ago |
| 5062 | Plan a profit-oriented Amazon boutique-product operating rhythm from selection gates through precise traffic tests, conversion validation, bid control, and cautious scaling. | xjli360/ | 247 | — | ~552 | Automated safety check: Pass | MIT | 11 days ago |
| 5063 | Assess an Amazon boutique business model through differentiated demand, pricing room, saturation, tail conversion, market health, capital turnover, and downside controls. | xjli360/ | 247 | — | ~538 | Automated safety check: Pass | MIT | 11 days ago |
| 5064 | Reverse-engineer an Amazon breakout case by testing competing explanations across product innovation, brand, keyword breadth, organic visibility, timing, variants, promotions, returns, and compliance. | xjli360/ | 247 | — | ~540 | Automated safety check: Pass | MIT | 11 days ago |
| 5065 | Infer competitor keyword coverage from observable organic and sponsored positions, shared attributes, query patterns, and product relevance without claiming access to a competitor account. | xjli360/ | 247 | — | ~556 | Automated safety check: Pass | MIT | 11 days ago |
| 5066 | Build a first-pass Amazon competitor traffic network from high-relevance organic and sponsored query observations plus attribute-root exploration. | xjli360/ | 247 | — | ~531 | Automated safety check: Pass | MIT | 11 days ago |
| 5067 | Build an evidence-gated Amazon competitor traffic network with separate opportunistic exact, contested exact, attribute exploration, automatic discovery, and defense layers. | xjli360/ | 247 | — | ~554 | Automated safety check: Pass | MIT | 11 days ago |
| 5068 | Diagnose weak Amazon conversion product-first by benchmarking comparable listings, market difficulty, price-value fit, visual differentiation, keyword precision, and placement mix. | xjli360/ | 247 | — | ~537 | Automated safety check: Pass | MIT | 11 days ago |
| 5069 | Set Amazon per-SKU inventory and advertising boundaries from realistic sales capacity, cash turnover, conversion, break-even acquisition cost, and portfolio risk. | xjli360/ | 247 | — | ~524 | Automated safety check: Pass | MIT | 11 days ago |
| 5070 | Build testable hypotheses for Amazon keyword relevance and ranking from conversion, clicks, orders, add-to-cart signals, listing semantics, and related-query behavior without claiming a proprietary… | xjli360/ | 247 | — | ~549 | Automated safety check: Pass | MIT | 11 days ago |
| 5071 | Turn competitor keyword observations and verified product attributes into separate exact, exploratory, listing, and backend keyword maps with explicit inclusion and exclusion reasons. | xjli360/ | 247 | — | ~540 | Automated safety check: Pass | MIT | 11 days ago |
| 5072 | Design an evidence-gated Amazon new-product ad launch with precise keyword selection, small coherent groups, controlled traffic acquisition, placement learning, and profit-aware scaling. | xjli360/ | 247 | — | ~562 | Automated safety check: Pass | MIT | 11 days ago |
| 5073 | Estimate Amazon operating difficulty from comparable-product sales distribution, low-review performance, ad dependence, store constraints, returns, and inventory break-even rather than headline… | xjli360/ | 247 | — | ~560 | Automated safety check: Pass | MIT | 11 days ago |
| 5074 | Design a compliant Amazon organic-rank experiment around relevant high-converting queries, variant fit, controlled ad support, and incremental-profit checks. | xjli360/ | 247 | — | ~529 | Automated safety check: Pass | MIT | 11 days ago |
| 5075 | Assess paid-versus-organic Amazon order contribution with whole-ASIN economics, cannibalization tests, query relevance, and time-window controls instead of subtracting attributed ad orders… | xjli360/ | 247 | — | ~560 | Automated safety check: Pass | MIT | 11 days ago |
| 5076 | Improve Amazon conversion by mining verified customer language, repositioning a product around a defensible benefit, and aligning images, title, bullets, and precise traffic in a controlled test. | xjli360/ | 247 | — | ~547 | Automated safety check: Pass | MIT | 11 days ago |
| 5077 | Find defensible Amazon niches inside competitive categories by combining differentiated product slices, low-review performance, ad-efficiency proxies, and evidence-quality checks. | xjli360/ | 247 | — | ~543 | Automated safety check: Pass | MIT | 11 days ago |
| 5078 | Screen an Amazon niche whose demand window, differentiated slice, low-review competition, conservative stocking, and operational follow-through must all align before launch. | xjli360/ | 247 | — | ~532 | Automated safety check: Pass | MIT | 11 days ago |
| 5079 | Control Amazon spread-model advertising around per-SKU break-even, conservative inventory, precise keyword tests, uniform group logic, and low-touch exception management. | xjli360/ | 247 | — | ~540 | Automated safety check: Pass | MIT | 11 days ago |
| 5080 | Design an Amazon spread-model portfolio that limits per-SKU inventory and ad exposure while aggregating profit across validated non-standardized product opportunities. | xjli360/ | 247 | — | ~541 | Automated safety check: Pass | MIT | 11 days ago |
| 5081 | Pre-screen Amazon spread-model product ideas by demand timing, market depth, differentiated slices, operating difficulty, conservative sales capacity, and inventory exposure. | xjli360/ | 247 | — | ~552 | Automated safety check: Pass | MIT | 11 days ago |
| 5082 | Assemble a repeatable evidence pipeline covering demand mining, side-by-side competitive teardown, and review-driven pain-point extraction before drafting Amazon listing copy and images meant to be… | xjli360/ | 247 | — | ~657 | Automated safety check: Pass | MIT | 11 days ago |
| 5083 | Screen a weather- or event-triggered demand spike for Amazon product opportunities by checking local supply-capacity gaps, installation or usage-friction barriers, and one's own supply-chain… | xjli360/ | 247 | — | ~666 | Automated safety check: Pass | MIT | 11 days ago |
| 5084 | Find the search-result position where an Amazon Sponsored Products keyword converts best per unit cost by logging position, click-through, conversion and bid over time, comparing the listing with… | xjli360/ | 247 | — | ~822 | Automated safety check: Pass | MIT | 11 days ago |
| 5085 | Decide whether a small FBM or light-FBA seller should enter an Amazon sub-category by reading demand versus competition bars, seller count against new-brand and new-ASIN share, return reasons that… | xjli360/ | 247 | — | ~850 | Automated safety check: Pass | MIT | 11 days ago |
| 5086 | Validate each listing or advertising change on Amazon by recording the change and its previous value, sampling organic and sponsored keyword positions for the main terms before and after under the… | xjli360/ | 247 | — | ~777 | Automated safety check: Pass | MIT | 11 days ago |
| 5087 | Discover and tier keywords for an Amazon product by combining long-tail expansion, search-suggestion checks, related-term tools and Brand Analytics based converting-term lookups on comparable ASINs… | xjli360/ | 247 | — | ~810 | Automated safety check: Pass | MIT | 11 days ago |
| 5088 | Screen Amazon sub-markets for a capital-constrained seller by capping demand, checking top-listing concentration against the market average, filtering out seasonal curves, reading new-product share… | xjli360/ | 247 | — | ~806 | Automated safety check: Pass | MIT | 11 days ago |
