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Get top charts

get_charts
Read-onlyIdempotent

Ranked top-chart entries (App summary plus rank) for a store. type is free/paid/grossing (Apple also supports new/newfree/newpaid). category is an Apple genre id (e.g. 6007) or a Google category constant (e.g. PRODUCTIVITY); omit for the overall chart. Google list() may return an empty array with meta.stale=true when a region is broken.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeNoChart type: free, paid, grossing (Apple also: new, newfree, newpaid). Default free.
limitNoApple practical max ~200; Google up to ~660 (usually <=500). Default 50.
storeYesTarget store.
countryNoISO-3166 alpha-2 storefront/region, lowercase. Defaults to us.
categoryNoApple genre id (e.g. 6007) or Google category constant (e.g. PRODUCTIVITY). Omit for overall chart.
fullDetailNoGoogle only; expensive. Default false.

TDQS

A3.6/5.0
Behavior4/5

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

The annotations already declare readOnlyHint and idempotentHint, and the description adds useful behavioral context: the potential empty array with meta.stale=true for Google when a region is broken, and the return format 'App summary plus rank'. This goes beyond what annotations alone provide.

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 concise (three sentences) and front-loaded with the core purpose. It is mostly efficient, though the phrase 'Google list()' is slightly confusing since the tool is named get_charts, and could distract the agent.

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

Completeness3/5

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

The description provides store-specific nuances and a caveat, but with no output schema it remains vague about the exact structure of returned entries. Saying 'App summary plus rank' is a decent high-level indication, but not fully complete for an agent to anticipate the response shape.

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 baseline is 3. The description restates parameter meanings (type, category) but adds no new details beyond the schema. The only extra nugget is 'omit for the overall chart', which is already present in the schema.

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

Purpose5/5

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

The description clearly states the tool's purpose: returning ranked top-chart entries (App summary plus rank) for a store. This is a specific and concrete description that distinguishes it from sibling tools that focus on individual app details, ASO rank, or categories.

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?

The description does not provide any guidance on when to use this tool versus alternatives. It explains parameter semantics (type, category) but never mentions sibling tools like get_aso_rank or get_categories, nor does it state explicitly that this is the tool for store-wide charts.

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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TDQS

A4.1/5.0
Disambiguation5/5

Each tool targets a distinct data resource: app details, reviews, permissions, data safety, charts, categories, developer, similar apps, search, autocomplete, and ASO keyword/rank tools. Even get_app vs get_apps_batch is clearly separated by single vs batch/bundleId lookups.

Naming Consistency4/5

Most tools follow a get_* verb_noun pattern (get_app, get_charts, get_developer), but autocomplete_suggest and search_apps deviate slightly. The style is otherwise consistent with clear snake_case naming.

Tool Count5/5

13 tools is well within the ideal range for a store data API serving both Apple and Google. Each tool covers a distinct aspect, and none are redundant or excessive.

Completeness4/5

The tool set covers all major read-only store data needs: search, detailed app info, reviews, charts, categories, developer, similar apps, and ASO insights. Minor gaps include lack of time-series rank tracking and no dedicated changelog endpoint, but version history is included in get_app.