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Cashback rates by store ID

get_cashback_rates_by_store_id
Read-onlyIdempotent

Returns the current online and in-store cashback rates from every cashback portal for one store identified by its numeric store_id, so the user can compare every portal and see the best. Use it only when a store_id is already known from an earlier result (a store, deals, favorites or alerts response). When the user gives a store name instead, call get_cashback_rates_by_store_name directly — do not look the id up first. Returns an error when the id does not exist. Rates reflect GotCashback's current data, refreshed several times a day. Present every returned portal's rate to the user (a table with a link column, not only the best one) and always show each rate's 'url' as a clickable link — cashback is only credited when the user clicks through it.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
store_idYesGotCashback's numeric store_id, taken from an earlier result (a store, cashback rate, gift card, deals, favorites or alerts response). If you only have a store name, use the by-name tool instead.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
storeNoA store (retailer) in one country, with its current cashback rates when returned by a cashback tool.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.9/5.0
Behavior5/5

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

Annotations already indicate readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds meaningful behavior beyond annotations: it returns an error for nonexistent ids, rates are refreshed several times a day, and every portal's rate must be presented with clickable url links because cashback only credits on click-through. No contradiction with annotations.

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?

The description is front-loaded with the core purpose, and every subsequent sentence adds necessary operational or selection detail. Although longer than minimal descriptions, the extra length is justified by the crucial display/click-through requirement and sibling routing guidance.

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?

The tool is simple (one parameter) and has both output schema and annotations, so the description does not need to restate return structures. It covers selection context, error behavior, data freshness, and required presentation behavior, making it complete for correct agent invocation.

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 100%, so the schema already fully documents store_id. The description adds practical meaning by reinforcing that the id must be numeric, must come from an earlier result, and that a store-name input should route to the by-name sibling instead.

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?

The description states a specific verb ('Returns'), resource ('cashback rates from every cashback portal for one store'), and scope ('one store identified by its numeric store_id'). It also explicitly distinguishes this tool from get_cashback_rates_by_store_name, making the purpose unambiguous.

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?

The description gives clear when-to-use guidance: only when a store_id is already known from an earlier result. It also states the exclusion condition and alternative directly: when the user gives a store name, call get_cashback_rates_by_store_name and do not look the id up first.

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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TDQS

A4.4/5.0
Disambiguation4/5

Most tools target a clearly distinct resource and action, and the descriptions carefully cross-reference when to use each one. The main risk is the similar get_stores_by_name, get_cashback_rates_by_store_name, and get_gift_cards_by_store_name names, though their descriptions do a good job of separating identity, cashback rates, and gift cards.

Naming Consistency4/5

The naming follows a mostly consistent get_<resource>_by_<selector> pattern with clear verb prefixes for mutations like set, remove, and toggle. Minor inconsistencies exist, such as get_portal_by_id (singular) versus get_portals_by_name (plural), and the get_my_* cluster for account tools.

Tool Count4/5

Eighteen tools is slightly above the ideal 3-15 range, but the count is justified by the breadth of the domain: store comparison, brand and category deals, gift cards, portals, countries, and user account features. Each tool has a distinct purpose, so the set does not feel genuinely bloated.

Completeness4/5

The tool surface covers the main workflows well: finding cashback by store, brand, or category, comparing gift cards and portls, browsing countries and stores, and managing favorites, alrts, and profile. Minor gaps exist, such as no direct way to rank all stores in a country by cashback rate without per-store lookups, but agents can work around these.

Resources