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Appfollow Reviews

appfollow_reviews
Read-onlyIdempotent

Recent App Store / Google Play reviews for an app. Returns author, star rating, title, text, date, app version, store, and whether the developer replied. Example: appfollow_reviews({ app_id: "1038369065", country: "us", _apiKey: "your-token" }). app_id is the store external id — App Store numeric id (e.g. "1038369065") or Google Play package name (e.g. "com.instagram.android").

Input Schema

NameRequiredDescriptionDefault
toNoEnd date YYYY-MM-DD (optional; defaults to today).
fromNoStart date YYYY-MM-DD (optional; defaults to 30 days ago).
app_idYesApp store external id: App Store numeric id (e.g. "1038369065") or Google Play package name (e.g. "com.instagram.android").
_apiKeyYesAppFollow API token (generate on the API management page in your AppFollow account).
countryNoTwo-letter country/store code, e.g. "us", "gb". Optional (default "us").

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.5/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, and non-destructive behavior, lowering the burden. The description adds useful behavioral context by listing the fields returned, clarifying the app_id formats, and giving a concrete call example. It does not mention pagination or rate limits, but the annotation coverage makes this acceptable.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is compact, front-loaded with the core purpose, then return fields, then an example, then app_id clarification. Some wording duplicates schema content, but every sentence is informative and there is no fluff.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a read-only tool with 5 well-documented parameters and no output schema, the description is largely complete: it gives required params, app_id formats, an example, and the return fields. Minor gaps such as pagination/limits and explicit sibling differentiation do not prevent an agent from invoking the tool correctly.

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 schema already documents all 5 parameters. The description mostly restates the app_id semantics found in the schema and provides an example that mirrors the schema example, adding little meaning beyond what structured data already provides.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb and resource: it returns recent App Store / Google Play reviews for an app, and enumerates the returned fields (author, star rating, title, text, date, app version, store, developer reply). It is clear about what the tool does, though it does not explicitly distinguish itself from the sibling appfollow_ratings.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no guidance on when to choose this tool instead of an alternative, such as appfollow_ratings for aggregate rating data. The example shows how to invoke the tool but does not provide a decision rule, context for when it applies, or exclusions.

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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