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Set a store alert

set_store_alert
Idempotent

Creates or updates an alert that emails the signed-in user when a store's cashback rate or gift card discount reaches the threshold percent or higher. Use it for 'alert me when Nike cashback hits 10%' or 'tell me when Target gift cards are 15% off'. Re-saving an existing alert updates its threshold and re-arms it. At most 10 active alerts per user. Needs the store_id: take it from an earlier result, or find it with get_stores_by_name (optionally with country_code). Requires OAuth sign-in with a GotCashback account and the 'alerts' scope; anonymous callers are prompted to authorize.

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.
alert_typeYesAlert type: 'cashback' (fires on the store's best cashback rate) or 'gift_card' (fires on the store's best gift card discount)
threshold_percentYesFire when the rate/discount reaches this percent or higher (greater than 0, at most 100), e.g. 10 for 10%

Schema Changelog

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

  1. First observed

TDQS

A4.5/5.0
Behavior5/5

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

The description adds substantial behavioral information beyond the annotations: the alert sends email, re-saving updates and re-arms the alert, there is a hard limit of 10 active alerts, and OAuth with the 'alerts' scope is required. This gives an agent important side-effect and precondition knowledge that annotations do not convey, and it does not contradict the 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 five concise sentences with the core behavior first, followed by memorable examples, lifecycle semantics, limits, and prerequisites. Every sentence carries distinct information and there is no filler or restatement of the schema.

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 mutation tool with no output schema, it covers all prerequisites needed to call it correctly: store_id resolution, auth scope, the maximum number of alerts, and what re-saving does. An agent has enough to decide when to use it and how to construct a valid invocation.

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?

The input schema already documents all three parameters in detail with 100% coverage, so the baseline is 3. The description adds useful operational framing—store_id provenance, re-saving semantics, and alert limits—but does not materially extend the parameter-level definitions already present in the schema.

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 opens with a clear verb-plus-resource: 'Creates or updates an alert' and specifies exactly what triggers it (cashback rate or gift card discount reaching a threshold. The examples like 'alert me when Nike cashback hits 10%' remove ambiguity, and the create/update operation is clearly distinct from sibling get/remove alert tools.

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?

It provides explicit use cases and a direct pointer to get_stores_by_name for resolving a store_id, and notes the required OAuth scope. It stops short of explicitly contrasting this tool with get_my_alerts or remove_store_alert, but the usage context is clear enough for an agent to select it.

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

A4.6/5.0
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