LemmeBuyIt

find_flips

Read-only

Find profitable resale candidates at a retailer in one call. Returns product families (variants collapsed) from the refreshed catalog ranked by ROI after marketplace fees, priced against the better of the live Amazon buy box and the Walmart cross-match (each row names the winning marketplace), with dead / parked-at-MSRP / case-pack / mismatched listings removed and a BUY or THIN call on every row, plus a coverage summary. Candidates are not gated on an on-sale flag: any price-changed item that clears the ROI screen surfaces. Set window:"today" for the daily-deals report (items refreshed today). Set retailer_id to "all" to scan across stores. To scan a whole merchandising category (e.g. every shoe/apparel or electronics store, including feed-based stores the daily scan misses), set retailer_id:"all" and pass vertical (e.g. "shoes_apparel"). Paid tiers page the full ranked rundown via meta.next_cursor; Free gets a top-10 taste with a locked-BUY upgrade hint. These are paper calls: verify live before buying.

Input Schema

TableJSON Schema

Name	Required	Description
`brand`	No	Brand filter (exact match).
`limit`	No	Rows per page. Default 25, max 100. Free tier is capped to the top 10.
`cursor`	No	Pagination cursor. Omit for the first page; then pass the prior response's meta.next_cursor to page through the full ranked rundown (paid tiers only).
`window`	No	Time window for candidates. "today" = items refreshed since 00:00 UTC today (the daily-deals report); "week" = last 7 days; "all" (default) = the full refreshed catalog. Candidates are not gated on an on-sale flag - any price-changed item that clears the ROI screen surfaces. Sales rank (BSR) is never a filter.
`min_net`	No	Minimum net profit per unit in USD. Default 3.00.
`min_roi`	No	Minimum ROI after fees, as a fraction (0.20 = 20%). Default 0.20.
`category`	No	Category filter (exact match).
`vertical`	No	Scan every store in a merchandising vertical (10-41 stores) instead of the daily-deals changes feed. Covers feed-based stores that the "all" changes scan misses. Inherently cross-retailer: when set, retailer_id is ignored and the scan always spans the vertical's member stores (set retailer_id:"all"). Use for "find shoe deals / apparel flips / electronics to resell" style asks.
`max_price`	No	Maximum retailer buy price (USD).
`min_price`	No	Minimum retailer buy price (USD).
`retailer_id`	Yes	Retailer id (e.g. "kohls", "walmart"), or "all" to scan across stores and merge the results. For a whole merchandising category (e.g. every shoe/apparel store), set retailer_id:"all" and pass `vertical`.
`include_thin`	No	Include THIN rows (profitable but under min ROI). Default false.
`referral_pct`	No	Marketplace referral fee as a fraction of resale price. Default 0.20.
`fulfillment_fee`	No	Flat per-unit fulfilment fee in USD. Default 5.00.

Schema Changelog

Changes observed during successful MCP inspections.

Changed3 schema fields changedSep 29, 2026

addedInput schema / properties / cursor

Added value: +{
+  "description": "Pagination cursor. Omit for the first page; then pass the prior response's meta.next_cursor to page through the full ranked rundown (paid tiers only).",
+  "type": "string"
+}

changedInput schema / properties / limit / description

Previous value: -"Number of ranked rows to return. Default 25."New value: +"Rows per page. Default 25, max 100. Free tier is capped to the top 10."

changedInput schema / properties / window / description

Previous value: -"Time window for candidates. \"today\" = on-sale items updated since 00:00 UTC today (the daily-deals report); \"week\" = last 7 days; \"all\" (default) = full on-sale catalog. Sales rank (BSR) is never a filter."New value: +"Time window for candidates. \"today\" = items refreshed since 00:00 UTC today (the daily-deals report); \"week\" = last 7 days; \"all\" (default) = the full refreshed catalog. Candidates are not gated on an on-sale flag - any price-changed item that clears the ROI screen surfaces. Sales rank (BSR) is never a filter."

Changed1 schema field changedSep 29, 2026

changedInput schema / properties / min_roi / description

Previous value: -"Minimum ROI after fees, as a fraction (0.30 = 30%). Default 0.30."New value: +"Minimum ROI after fees, as a fraction (0.20 = 20%). Default 0.20."

Changed2 schema fields changedSep 29, 2026

changedInput schema / properties / retailer_id / description

Previous value: -"Retailer id (e.g. \"kohls\", \"walmart\"), or \"all\" to scan several large retailers and merge the results."New value: +"Retailer id (e.g. \"kohls\", \"walmart\"), or \"all\" to scan across stores and merge the results. For a whole merchandising category (e.g. every shoe/apparel store), set retailer_id:\"all\" and pass `vertical`."

addedInput schema / properties / vertical

Added value: +{
+  "description": "Scan every store in a merchandising vertical (10-41 stores) instead of the daily-deals changes feed. Covers feed-based stores that the \"all\" changes scan misses. Inherently cross-retailer: when set, retailer_id is ignored and the scan always spans the vertical's member stores (set retailer_id:\"all\"). Use for \"find shoe deals / apparel flips / electronics to resell\" style asks.",
+  "enum": [
+    "shoes_apparel",
+    "general_merchandise",
+    "home_garden",
+    "electronics",
+    "sports_outdoors",
+    "health_beauty",
+    "toys_games",
+    "food_supplements",
+    "crafts_hobbies",
+    "bags_travel"
+  ],
+  "type": "string"
+}

Changed2 schema fields changedSep 29, 2026

removedInput schema / properties / max_sales_rank

Removed value: -{
-  "description": "Maximum Amazon sales rank (BSR). Default 250000.",
-  "maximum": 9007199254740991,
-  "minimum": 0,
-  "type": "integer"
-}

addedInput schema / properties / window

Added value: +{
+  "description": "Time window for candidates. \"today\" = on-sale items updated since 00:00 UTC today (the daily-deals report); \"week\" = last 7 days; \"all\" (default) = full on-sale catalog. Sales rank (BSR) is never a filter.",
+  "enum": [
+    "all",
+    "today",
+    "week"
+  ],
+  "type": "string"
+}

AddedSep 28, 2026

TDQS

A4.6/5.0

Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations only declare readOnly/destructive=false, and the description adds substantial behavior: variants collapsed, ROI net of fees, dead/MSRP/case-pack/mismatch filtering, non-reliance on sale flags, paid-vs-free pagination and row caps, and the 'paper calls: verify live before buying' caveat. This goes well beyond what annotations already provide.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded with purpose, then a tight behavioral paragraph, then parameter-combination guidance, and closing caveat. Dense but every clause carries useful information for a 14-parameter tool; minor redundancy with the schema descriptions keeps it from a 5.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given a 14-parameter tool with no output schema and minimal annotations, the description covers return shape (product families, coverage summary, BUY/THIN), pagination behavior, free-tier limits, filtering behavior, and a purchase-safety caveat. Nothing an agent needs in order to invoke it correctly is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is already 100%, so the baseline is 3. The description still earns extra credit by explaining the interaction between parameters (retailer_id:'all' plus vertical spans a vertical's member stores, retailer_id ignored in that mode) and by tying window/retailer_id/vertical to specific use cases, which individual schema descriptions do not fully connect.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb+resource ('Find profitable resale candidates') and details exactly what is returned (collapsed product families, ROI-ranked, winning marketplace per row, BUY/THIN call, coverage summary). An agent can distinguish this from the sibling catalog/price-history tools without opening any schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives clear contextual triggers: use window:'today' for daily-deals, retailer_id:'all' for cross-store scanning, and retailer_id:'all' + vertical for whole merchandising categories including feed-based stores. It does not explicitly name when a sibling tool is the better choice, but the when-to-use conditions are concrete and actionable.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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