get_my_profileReturns the signed-in user's GotCashback profile (name, email, avatar). Use it when the user asks who they are signed in as or wants their account details. Requires OAuth sign-in with a GotCashback account; anonymous callers are prompted to authorize. All comparison tools work without signing in. Scope: 'profile'.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already mark the tool as readOnly, idempotent, and non-destructive. The description adds important behavioral context beyond those annotations: it requires OAuth sign-in with a GotCashback account, anonymous callers are prompted to authorize, and the required scope is 'profile'. This gives the agent a clear picture of what will happen at invocation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured and front-loaded with the core purpose and return fields. The use-case and auth guidance are useful, but the sentence about all comparison tools working without signing in is somewhat tangential to this specific tool, making it slightly less crisp than it could be.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter, read-only profile retrieval tool, the description is complete: it names the resource, the returned fields, the trigger conditions for use, the authentication requirement, and the OAuth scope. No output schema is needed because the description already states what data the user will receive.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, so the baseline is 4. The description does not need to explain parameter semantics, and it correctly implies that no arguments are required to retrieve the signed-in user's profile.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with a specific verb ('Returns') and names the exact resource: the signed-in user's GotCashback profile, including the fields (name, email, avatar). It also states clear use cases ('asks who they are signed in as or wants their account details'), which distinguishes it from sibling tools like get_my_alerts or get_my_favorite_stores.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly says when to use this tool: when the user asks who they are signed in as or wants their account details. It also states the auth prerequisite and the fact that anonymous callers are prompted to authorize. However, it does not explicitly name a sibling alternative or provide a when-not-to-use condition, so it falls just short of full routing guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
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.
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.
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.
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.