Scrape and extract application reviews from both the Google Play Store and the Apple App Store.
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Average 3.7/5 across 3 of 3 tools scored.
Each tool has a distinct purpose. The two review tools are clearly separated by store (Apple vs. Google), and usage_statistic is obviously about API rate limits, so there is no ambiguity between tools.
The two review tools follow a consistent get_<store>_reviews pattern, but usage_statistic breaks the pattern by using a noun-only name with no verb and no parallel structure.
Three tools is a reasonable count for a simple reviews server. However, usage_statistic seems unrelated to the core purpose, making the set feel slightly padded.
The server covers the primary need of fetching reviews from both major app stores. Minor gaps include lack of filtering or rating summaries, and usage_statistic is a non-domain operation that does not contribute to review workflows.
get_app_store_reviewsAInspectGet reviews for a specific app from the Apple App Store.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | App Store app ID (e.g. 1462715669) | |
| page | No | Page number (e.g. 1) | |
| sort | No | Sort order | |
| country | Yes | Country code (e.g. 'id') |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It only says 'Get reviews' without mentioning pagination, sorting behavior, country-specific filtering, return format, or any constraints. The read-only nature is implied but not elaborated, leaving the agent guessing about behavior.
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, 11-word sentence that is front-loaded and free of filler. Every word earns its place, making it exceptionally concise and clear.
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?
Since there is no output schema, the description should clarify what 'reviews' includes (e.g., review text, ratings, metadata). It does not explain the response format, pagination, or that both id and country are required. Given the tool's complexity (4 parameters, no output schema), this is under-specified.
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?
Schema coverage is 100%, with each parameter having a description (e.g., 'App Store app ID', 'Sort order'). The description adds no extra parameter semantics, but the baseline of 3 is appropriate since the schema already provides sufficient meaning.
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 uses a specific verb ('Get'), a clear resource ('reviews'), and an explicit source ('Apple App Store'), which immediately distinguishes it from sibling tools like get_play_store_reviews (Google Play) and usage_statistic (usage stats). It precisely states what the tool does.
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 clear platform context ('Apple App Store'), making it obvious when to use this tool (for iOS app reviews) versus the Android sibling. However, it does not explicitly name alternatives or state exclusions, so it falls short of a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_play_store_reviewsBInspectGet reviews for a specific app from the Google Play Store.
| Name | Required | Description | Default |
|---|---|---|---|
| num | No | Number of reviews to fetch (e.g. 10) | |
| lang | No | Language code (e.g. 'id') | |
| sort | No | Sort order | |
| appId | Yes | Play Store app ID (e.g. 'id.bmri.livin') | |
| rating | No | Specific rating to filter by (e.g. 1) | |
| country | No | Country code (e.g. 'id') |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavioral traits beyond the basic purpose. It only says 'Get' which implies a read-only operation, but provides no details on rate limits, pagination, or parameter interactions. There is no contradiction, but the disclosure is sparse.
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 sentence of ten words, which is exceptionally concise and front-loaded with the essential information. Every word serves the core purpose.
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 tool with six parameters and no output schema or annotations, the description is minimal but the schema provides rich parameter documentation. However, it lacks behavioral context such as sorting/filtering semantics or output expectations, making it adequate but not fully 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?
All six parameters have descriptions in the input schema, so the description does not need to explain them. However, the description adds no parameter-specific context beyond the schema, so it does not improve on the schema's coverage.
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 'Get reviews for a specific app from the Google Play Store', using a specific verb and resource. It distinguishes itself from the sibling 'get_app_store_reviews' by explicitly naming the Google Play Store.
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?
No guidance is provided about when to use this tool versus alternatives. It does not mention the sibling tools or any exclusions, leaving the agent to infer usage solely from the name.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
usage_statisticAInspectRetrieves the current user's API rate limits, including requests used and remaining requests.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden of behavioral disclosure. It discloses a read-only operation ('Retrieves') and returns specific fields. However, it does not explicitly state that it has no side effects, require authentication, or describe whether the rate limit data resets or is time-windowed. Some behavioral context is added, but it is not extensive.
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 sentence, front-loaded with the verb, and contains no filler. Every word contributes to understanding the tool's purpose and output.
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 tool with no parameters and no output schema, the description clearly explains what it returns. It lacks explicit mention of authentication or error conditions, but these are not critical for a simple retrieval tool. The description is sufficient for an agent to select and invoke the tool correctly.
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, and the schema is empty, so there is no parameter information to supplement. The description adds meaning about the output (usage and remaining requests), which is more than what the schema alone provides. Baseline for zero parameters is 4, and the description earns that.
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 a specific action ('Retrieves') and resource ('current user's API rate limits'), and it names the exact data provided ('requests used and remaining requests'). This distinguishes it from sibling tools about app store reviews, which are entirely unrelated.
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 implies the tool is used for checking API rate limits, providing clear context. It does not explicitly exclude alternatives or mention when-not-to-use, but the sibling tools are so dissimilar (reviews vs. rate limits) that usage intent is unambiguous.
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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