Skip to main content
Glama

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

A4.7/5.0
Behavior5/5

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

The annotations already declare readOnlyHint, idempotentHint, and destructiveHint, and the description adds meaningful behavioral context: it returns an error for a nonexistent id, rates are refreshed several times a day, and cashback is only credited when the user clicks the url link. This goes beyond the structured hints and is not contradictory.

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 appropriately sized and front-loaded: the core behavior appears first, followed by routing guidance, error/freshness information, and presentation instructions. Each sentence carries distinct, useful information with no filler or redundancy.

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 the tool has a single well-described parameter, a read-only/idempotent annotation set, an output schema, and clear sibling alternatives, the description fully covers what the agent needs: when to call it, when not to, what to expect, and how to present results. Nothing material is missing.

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%, so the parameter is already fully documented in the input schema. The tool description reaffirms that store_id is numeric and should come from an earlier result, but does not significantly extend what the schema already states; hence baseline 3 is appropriate.

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') and resource ('current online and in-store cashback rates from every cashback portal for one store identified by its numeric store_id'), making the tool's purpose immediately clear. It also differentiates from the sibling by explaining the store_id vs store_name lookup split.

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 explicit usage guidance: use only when a store_id is already known, and when only a store name is available, call get_cashback_rates_by_store_name directly without looking up the id first. This clearly routes the agent between two similar siblings and prevents unnecessary lookup steps.

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

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A4.6/5.0
Disambiguation5/5

Each tool targets a clearly distinct lookup or action: store names versus store ids, cashback versus gift cards, brand versus category versus store, and portals versus stores versus user account data. The descriptions also include explicit cross-references telling an agent which tool to prefer, so misselection is unlikely.

Naming Consistency5/5

Tool names follow a consistent get_/set_/remove_/toggle_ verb pattern with resource and qualifier suffixes like by_store_name, by_store_id, and by_country. Singular and plural resource names are used naturally and do not break the overall predictable convention.

Tool Count4/5

18 tools is slightly above the typical well-scoped range, mainly because of parallel by_name and by_id variants for stores, gift cards, and portals. However, each variant serves a distinct workflow and the overall count is coherent for a cashback-comparison and account-management server.

Completeness5/5

The surface covers the full range of the domain: cashback rate lookups, gift card comparisons, brand/category deals, store and portal browsing, payout term checks, and user favorites/alerts with create, update, and delete operations. There are no obvious dead ends, and the cross-references between tools make workflows like finding a store_id and then setting an alert seamless.

Resources