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Category totals

sensortower_store_summary
Read-only

Get category-wide download and revenue totals over time, not per-app, with optional game genre breakdown and revenue converted from cents.

Instructions

Category-level download and revenue totals over time -- the whole category, not per-app. games=true switches to the games_breakdown endpoint (same shape, game genres instead of store categories). Revenue converted from cents.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
osNoStore to query. This endpoint has no unified variant.ios
gamesNoUse games_breakdown instead of store_summary.
limitNoKeep at most this many rows.
fieldsNoComma-separated allowlist of output fields. Strongly recommended: SensorTower rows are wide.
formatNoOutput encoding. csv is markedly cheaper in tokens for wide, flat results.
dry_runNoPrint the URL that would be called (token redacted) and charge 0 requests.
end_dateYesEnd of the window, YYYY-MM-DD (inclusive).
countriesNoComma-separated ISO country codes, or "WW" for worldwide.US
categoriesYesComma-separated category ids or slugs.
start_dateYesStart of the window, YYYY-MM-DD (inclusive).
date_granularityNoWiden this rather than looping over dates -- each request costs the same.monthly

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already establish readOnlyHint=true and openWorldHint=true, so the safety profile is covered. The description adds real behavioral context beyond that: games=true silently redirects to the games_breakdown endpoint with the same shape, and revenue is converted from cents. It omits any cost/rate-limit note despite dry_run existing in the schema.

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?

Three sentences, front-loaded with the core purpose, then the games branch, then the units note. Mostly earns its place, though the games-endpoint sentence partly duplicates the schema's games field description.

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, 11-param tool with no output schema, the description covers purpose, endpoint switching, and unit conversion. It stops short of describing the return shape beyond 'same shape,' but the annotations carry the safety profile, so an agent has enough to call it 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 baseline is 3. The description only marginally adds value: the games endpoint switch is already documented in the schema's games field, while 'revenue converted from cents' is the one genuinely new semantic detail not present in any parameter description.

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?

States a specific verb+resource ('Category-level download and revenue totals over time') and immediately disambiguates scope: 'the whole category, not per-app.' This cleanly separates it from the many app-level siblings (app_estimates, app_active_users, etc.) without opening a schema.

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

Usage Guidelines4/5

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

The 'not per-app' clause implies when to reach for app-level siblings instead, and it explains the games=true branch. However it never names a specific alternative tool or states explicit exclusions (e.g. vs market_size), so routing relies partly on inference.

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