The stored listing (name, subtitle, description, rating, price) for a tracked app.
| Name | Required | Description | Default |
|---|---|---|---|
| app_key | Yes | An app key from list_tracked_apps, e.g. 'ios:123456789'. | |
| country | No | Two-letter storefront code, e.g. 'us', 'de'. Defaults to 'us'. |
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?
With no annotations, the description carries the full burden. It describes a read operation ('stored listing') but does not explicitly state that it is read-only or has no side effects. No error behavior or data source is disclosed.
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 a single, concise sentence that immediately conveys the tool's purpose and the content of the returned listing. No filler or redundant wording.
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?
The list of returned fields gives useful context for the expected output, and the parameters are well-explained in the schema. Minor gaps include no mention of error cases or whether the listing is return-only, but the tool's simplicity keeps it mostly complete.
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 schema provides good coverage for both parameters: app_key has an example and country has a default and description. The description adds no extra semantic detail beyond the schema, so it meets the baseline.
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 clearly states the tool retrieves a stored listing for a tracked app and lists the specific fields (name, subtitle, description, rating, price). The verb 'get' and resource 'listing' are explicit, and the tool is distinguished from siblings like get_growth_plan or list_tracked_apps.
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 provides no guidance on when to use this tool versus alternatives, such as when to prefer get_listing over list_tracked_apps or search_keyword. No context or preconditions are mentioned.
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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Each tool targets a clearly distinct concern: growth plans, listings, review verdicts, tracked keywords, app lists, and live keyword search. There is no functional overlap between tools like get_tracked_keywords and search_keyword because one reports watchlist history and the other performs ad-hoc research.
Tool names follow a consistent verb_noun pattern: get_* for retrieving stored entities, list_* for enumerating apps, and search_keyword for live research. The naming is predictable and immediately conveys each tool's purpose.
Six tools is a well-scoped set for an ASO-focused server, covering the main read-only surfaces without redundancy or unnecessary bulk. Each tool earns its place and the count feels appropriate for the domain.
The tool surface covers the core ASO workflows: viewing tracked apps, listing metadata, review verdicts, keyword watchlists, and performing live keyword research. Given the apparent read-only analytics scope, there are no obvious missing operations.