earnrate

Best cards for a purchase

best_cards_for

Read-only

Ranks every card earnrate knows, not only the user's, for one purchase or category, each set up at its best (the right category pick, activated, cap unused), with its annual fee and what earning the rate takes. Use it for questions like "what's the best card for groceries?" or "which card should I get for Amazon?". It needs no wallet. For which of the user's own cards to use, call best_card_for_purchase instead. Mention the annual fee and any conditions alongside each card.

Input Schema

Name	Required	Description
`kind`	No	cash: cash back cards only. points: points and miles cards only.
`amount`	No	Purchase amount in US dollars, if known.
`issuer`	No	Only this issuer's cards.
`channel`	No	How the purchase is made. Omit if unknown; the answer says what it assumed.
`business`	No	Business cards instead of personal ones.
`category`	No	A spending category: dining (Restaurants), dining.fast_food (Fast food), grocery.supermarket (Supermarkets), grocery.online (Online grocery and delivery), superstore (Superstores), warehouse_club (Warehouse clubs), convenience_store (Convenience stores), gas (Gas stations), gas.grocery_store (Gas at grocery stores), gas.superstore (Gas at superstores and warehouse clubs), ev_charging (EV charging), transit (Transit), transit.rideshare (Rideshare and taxis), travel (Travel), travel.flights (Flights), travel.hotels (Hotels), travel.car_rental (Car rental), travel.cruise (Cruises), streaming (Streaming services), tv_internet (TV and internet service), phone (Cell phone service), utilities (Home utilities), drugstore (Drugstores and pharmacies), movie_theaters (Movie theaters), entertainment (Live entertainment and events), fitness (Gyms and fitness), department_store (Department stores), clothing (Clothing stores), electronics (Electronics stores), sporting_goods (Sporting goods stores), home_improvement (Home improvement), furniture (Furniture stores), online_retail (Online retail), office_supply (Office supply stores), shipping (Shipping and couriers), online_advertising (Social media and search advertising), other (Everything else).
`merchant`	No	Merchant name or web address as the user would say it or see it, e.g. "Whole Foods" or "delta.com".
`valuation`	No	flat (default): points at their cash-out value, about 1¢. points-heavy: Amex MR and Chase UR at 1.7¢, for people who transfer points to airlines and hotels.
`memberships`	No	Memberships the user has, such as amazon-prime. Rates that need one they don't have are listed separately.
`noAnnualFee`	No	Only cards with no annual fee.

Output Schema

Name	Required	Description	Default
`ranked`	Yes
`excluded`	Yes
`merchant`	Yes
`warnings`	Yes
`assumptions`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

Changed2 schema fields changedNov 1, 2026

changedInput schema / properties / category / description

Previous value: -"A spending category: dining (Restaurants), dining.fast_food (Fast food), grocery (Grocery), grocery.supermarket (Supermarkets), grocery.online (Online grocery and delivery), superstore (Superstores), warehouse_club (Warehouse clubs), convenience_store (Convenience stores), gas (Gas stations), gas.grocery_store (Gas at grocery stores), gas.superstore (Gas at superstores and warehouse clubs), ev_charging (EV charging), transit (Transit), transit.rideshare (Rideshare and taxis), travel (Travel), travel.flights (Flights), travel.hotels (Hotels), travel.car_rental (Car rental), travel.cruise (Cruises), streaming (Streaming services), tv_internet (TV and internet service), phone (Cell phone service), utilities (Home utilities), drugstore (Drugstores and pharmacies), movie_theaters (Movie theaters), entertainment (Live entertainment and events), fitness (Gyms and fitness), department_store (Department stores), clothing (Clothing stores), electronics (Electronics stores), sporting_goods (Sporting goods stores), home_improvement (Home improvement), furniture (Furniture stores), online_retail (Online retail), office_supply (Office supply stores), shipping (Shipping and couriers), online_advertising (Social media and search advertising), other (Everything else)."New value: +"A spending category: dining (Restaurants), dining.fast_food (Fast food), grocery.supermarket (Supermarkets), grocery.online (Online grocery and delivery), superstore (Superstores), warehouse_club (Warehouse clubs), convenience_store (Convenience stores), gas (Gas stations), gas.grocery_store (Gas at grocery stores), gas.superstore (Gas at superstores and warehouse clubs), ev_charging (EV charging), transit (Transit), transit.rideshare (Rideshare and taxis), travel (Travel), travel.flights (Flights), travel.hotels (Hotels), travel.car_rental (Car rental), travel.cruise (Cruises), streaming (Streaming services), tv_internet (TV and internet service), phone (Cell phone service), utilities (Home utilities), drugstore (Drugstores and pharmacies), movie_theaters (Movie theaters), entertainment (Live entertainment and events), fitness (Gyms and fitness), department_store (Department stores), clothing (Clothing stores), electronics (Electronics stores), sporting_goods (Sporting goods stores), home_improvement (Home improvement), furniture (Furniture stores), online_retail (Online retail), office_supply (Office supply stores), shipping (Shipping and couriers), online_advertising (Social media and search advertising), other (Everything else)."

changedInput schema / properties / category / enum

Previous value: -[
-  "dining",
-  "dining.fast_food",
-  "grocery",
-  "grocery.supermarket",
-  "grocery.online",
-  "superstore",
-  "warehouse_club",
-  "convenience_store",
-  "gas",
-  "gas.grocery_store",
-  "gas.superstore",
-  "ev_charging",
-  "transit",
-  "transit.rideshare",
-  "travel",
-  "travel.flights",
-  "travel.hotels",
-  "travel.car_rental",
-  "travel.cruise",
-  "streaming",
-  "tv_internet",
-  "phone",
-  "utilities",
-  "drugstore",
-  "movie_theaters",
-  "entertainment",
-  "fitness",
-  "department_store",
-  "clothing",
-  "electronics",
-  "sporting_goods",
-  "home_improvement",
-  "furniture",
-  "online_retail",
-  "office_supply",
-  "shipping",
-  "online_advertising",
-  "other"
-]New value: +[
+  "dining",
+  "dining.fast_food",
+  "grocery.supermarket",
+  "grocery.online",
+  "superstore",
+  "warehouse_club",
+  "convenience_store",
+  "gas",
+  "gas.grocery_store",
+  "gas.superstore",
+  "ev_charging",
+  "transit",
+  "transit.rideshare",
+  "travel",
+  "travel.flights",
+  "travel.hotels",
+  "travel.car_rental",
+  "travel.cruise",
+  "streaming",
+  "tv_internet",
+  "phone",
+  "utilities",
+  "drugstore",
+  "movie_theaters",
+  "entertainment",
+  "fitness",
+  "department_store",
+  "clothing",
+  "electronics",
+  "sporting_goods",
+  "home_improvement",
+  "furniture",
+  "online_retail",
+  "office_supply",
+  "shipping",
+  "online_advertising",
+  "other"
+]

First observedOct 31, 2026

TDQS

A4.5/5.0

Behavior4/5

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

Annotations already declare readOnlyHint=true and openWorldHint=false, so safety is covered; the description adds real context beyond that: it ranks cards outside the wallet, assumes each card is set up optimally (right category pick, activated, cap unused), and surfaces annual fee plus conditions. It does not describe result size, ordering depth, or rate limits, so it falls short of a 5.

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

Conciseness5/5

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

Front-loaded with the core behavior, then examples, then the alternative and a presentation instruction. Every sentence earns its place; the parenthetical about optimal setup is dense rather than padded.

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?

For a 10-parameter tool with an output schema and annotations, the description covers what it does, its key modeling assumption, the wallet-independence, and the sibling boundary. An agent has everything needed to select and call it correctly.

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

Parameters3/5

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

Schema description coverage is 100% with enums and per-parameter docs, so the schema carries parameter meaning and the baseline is 3. The description adds only indirect hints ("for one purchase or category", "the answer says what it assumed" is already in the schema) and no per-parameter guidance beyond that.

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 (ranks) and a precisely scoped resource: every card earnrate knows, not only the user's, for one purchase or category. It immediately distinguishes itself from the sibling best_card_for_purchase, so an agent can route correctly without opening either schema.

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

Usage Guidelines5/5

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

Gives explicit when-to-use examples ("what's the best card for groceries?", "which card should I get for Amazon?"), states a prerequisite explicitly negated ("It needs no wallet"), and names the alternative with the condition that selects it ("For which of the user's own cards to use, call best_card_for_purchase instead"). Nothing is left to inference.

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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