App Store + Google Play Data

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

Annotations already declare readOnlyHint and openWorldHint, so safety is covered. The description adds the useful detail that the response contains full metadata (name, developer, ratings, price, version, size, screenshots, store URL), but says nothing about behavior on missing/unknown app ids or whether results vary by storefront.

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?

Two tight sentences; the core purpose and the return payload are front-loaded and nothing is wasted.

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?

With no output schema, the field list compensates well for what the tool returns, and the schema handles the input side. Only missing is error/empty-result behavior, a minor gap for a simple read tool.

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 description coverage is 100%, so all four parameters are already documented including the app_id format examples and store enum. The description's identifier sentence largely restates the schema, though it does usefully tie the id format to the store value.

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?

States a specific verb+resource ('Full metadata for one app') and enumerates the fields returned, which distinguishes it from search_apps and list_categories. It stops short of naming siblings explicitly, so differentiation is implicit rather than stated.

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?

Gives identifier guidance ('use the numeric app id (iOS) or package name (Android)'), which is invocation guidance rather than when-to-use guidance. It never says when to prefer search_apps over get_app or what to do when you only have an app name.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

Annotations already declare readOnlyHint=true and openWorldHint=true, so safety is covered. The description adds genuine behavioral detail not in the structured fields: that results are paginated and that a has_more flag in the response signals termination — important since there is no output schema.

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?

Three short sentences, zero filler, with the resource and pagination model front-loaded before the sort guidance. Every clause carries actionable information.

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?

Given six parameters, no output schema, and an openWorld read, the description covers intent, sort choice, and pagination termination, but says nothing about the shape of a review record, behavior when an app_id is invalid, or store/country effects on results. Adequate but with visible gaps.

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 description coverage is 100%, so baseline is 3, but the description adds real semantic value the schema lacks: it explains what each sort mode is actually good for rather than just listing the enum, and it clarifies offset's role in a paging loop.

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 'Paginated user reviews,' identifying the resource and its paginated nature, and the required app_id plus pagination guidance makes clear it returns reviews for one app. It is clearly distinct from siblings like search_apps, get_app and top_charts, though the retrieval verb itself is only implied by the fragment.

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?

Gives concrete selection guidance for the sort parameter ('recent is best for monitoring new feedback; sort=helpful surfaces the loudest complaints') and an explicit pagination loop ('page with offset and stop when has_more is false'). It lacks any explicit when-not or sibling-routing statement, but usage context is clear.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

Annotations already declare readOnlyHint=true and openWorldHint=true, so safety is covered. The description adds the return shape (id and name) in the absence of an output schema, but says nothing about whether the list is locale-dependent, how large it is, or whether country/store change the result.

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?

A single economical sentence with the resource stated first and the purpose trailing after the em dash. Nothing is wasted, though the telegraphic style is slightly clipped.

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 simple read-only two-parameter lookup with full schema docs and safety annotations, this is nearly sufficient. The only material gap is whether the taxonomy varies by store or country, which an agent would want to know before caching or reusing ids.

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 both parameters fully described, including enum values and defaults, so the schema carries the meaning. The description adds no parameter-specific information such as whether country affects the returned categories.

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 names the resource (the store's category taxonomy) and the exact payload (id and name), so an agent knows precisely what it returns. It does not use an explicit verb like 'list', but the resource is unambiguous and clearly distinct from the app/review/chart siblings.

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?

It gives two concrete use cases: building filters and resolving a category id consumed by top_charts. That is a real routing signal to call this before top_charts, though it states no exclusions or prerequisites.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

Annotations already cover read-only and open-world safety. The description adds real value beyond them by disclosing that results use the store's own relevance ranking and come back as compact rows, which tells the agent not to expect full app records or a deterministic ordering.

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?

Two tight sentences, zero filler, with the core action front-loaded and the follow-up pointer second. Every clause earns its place.

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?

With no output schema, the description compensates by characterizing the return shape ('compact rows with the id') and its intended downstream use. An agent has enough to call it correctly; only the browse-vs-search distinction from siblings is missing.

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 description coverage is 100%, with lang, limit, store, country, and query all documented including defaults and enum values. The description only reinforces the keyword concept behind query and adds nothing on syntax or store/country interplay, so baseline 3 applies.

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?

States a specific verb and resource ('Search a store by keyword') plus the ranking behavior, and explicitly ties results to the get_app follow-up. It doesn't differentiate from siblings like top_charts or list_categories (browse vs. search), so it falls just short of a 5.

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 second sentence implies the workflow ('the id you need for get_app'), which is useful chaining guidance. However, there is no explicit statement of when to use this versus top_charts or list_categories, and no exclusion conditions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

The annotations already declare readOnlyHint=true and openWorldHint=true, so the safety profile is covered. The description adds that results are ranked and storefront-scoped, but it does not disclose pagination, rate limits, return ordering details, or other behavioral constraints beyond what the annotations provide.

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 two tight sentences with no filler. The core purpose is front-loaded, and the second sentence provides the useful collection enumeration without redundant explanation.

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 simple read-only rankings query with fully documented parameters and safety annotations, the description is largely complete. The main remaining gap is that there is no output schema and the description does not describe the returned row structure, though 'ranked top-chart lists' gives the agent enough to understand the result domain.

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 description coverage is 100%, so the baseline is 3. The description earns an upward adjustment by enumerating valid collection names per store, which adds meaningful semantics beyond the schema's generic 'Chart name' description.

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 states a specific resource and scope: ranked top-chart lists per storefront, with concrete iOS and Android collection names. It is clearly not a search, category-list, app-detail, or review tool, but it does not explicitly contrast itself with those sibling tools.

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 tells what chart collections exist, but it does not say when to use this tool versus search_apps, get_app, list_categories, or get_app_reviews. There is no explicit when/when-not guidance or alternative routing.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.