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datasets_apps_charts_search

Search daily top-chart snapshots from iOS App Store and Google Play. Filter by store, chart type, date, or app ID to find rankings and rank history over time.

Instructions

Search the app-charts dataset. Searches daily top-chart snapshots scraped from the iOS App Store and Google Play, stored in a search index (one document per chart × snapshot × rank). With no date the latest snapshot is returned (today's chart); pair app_id with sort=date_desc for an app's rank over time. Store enum: ios, android. Chart type enum: top_free, top_paid, top_grossing, new. Platform enum (Apple device platforms, ios charts only): phone, pad, mac. Sort enum: rank, rank_desc, date_desc.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
qNoFull-text query over chart-entry title and developer, max 256 characters
dateNoSnapshot date filter yyyy-MM-dd; defaults to the latest snapshot
pageNoPage number, defaults to 1
sortNoSort enum: rank, rank_desc, date_desc
storeNoStore enum: ios, android
app_idNoExact app filter — iOS numeric track id or Android package; pair with sort=date_desc for rank history
countryNoExact storefront country filter, max 128 characters
categoryNoStore category/genre filter, max 128 characters; empty for the overall charts
platformNoApple device-platform filter, iOS charts only; see platform enum above
page_sizeNoPage size, defaults to 20 and maxes at 100; page * page_size must be <= 10000
chart_typeNoChart enum: top_free, top_paid, top_grossing, new
collectionNoRaw store collection id filter (e.g. topgrossingapplications, GROSSING), max 128 characters

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed3 schema fields changedv1.17.5
    • addedInput schema / properties / chart_type / enum
      Added value: +[
+  "top_free",
+  "top_paid",
+  "top_grossing",
+  "new"
+]
    • addedInput schema / properties / sort / enum
      Added value: +[
+  "rank",
+  "rank_desc",
+  "date_desc"
+]
    • addedInput schema / properties / store / enum
      Added value: +[
+  "ios",
+  "android"
+]
  2. Changed1 schema field changed
    • addedInput schema / properties / platform
      Added value: +{
+  "description": "Apple device-platform filter, iOS charts only; see platform enum above",
+  "type": "string"
+}
  3. Addedv1.2.0

TDQS

A4.3/5.0
Behavior4/5

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

With no annotations, the description has the full burden and mostly carries it: it discloses the index structure ('one document per chart × snapshot × rank'), the default latest-snapshot behavior, and the rank-over-time usage pattern. It also flags that the platform filter applies only to iOS charts. It does not mention pagination limits or output shape, but for a search tool these are partially covered by the schema, so the provided behavioral detail is well beyond a bare minimum.

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 a compact paragraph that front-loads the core purpose and dataset origin, then moves to behavioral defaults and parameter combinations. The enum lists are partially redundant with the schema, costing a little efficiency, but the overall every-sentence-earns-its-place structure is strong. It stays well within a reasonable size for a 12-parameter tool.

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 12-parameter search tool with 100% schema description coverage and no output schema, the description supplies the key missing context: what the dataset consists of, how the search index is organized, and the important date/app_id behaviors. It does not explain return fields or pagination effects, but those are either in the schema or not required given the tool's read-only search nature. The description closes most of the gap left by the absent annotations.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the baseline is 3, but the description adds genuinely useful cross-parameter semantics: the date default behavior, the app_id + sort=date_desc combination for rank history, and the platform-is-iOS-only constraint. It also re-lists the enums, which is redundant but reinforces parameter choices. This adds meaning beyond the schema's individual field descriptions.

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 opens with 'Search the app-charts dataset' and explicitly defines the data source as 'daily top-chart snapshots scraped from the iOS App Store and Google Play', making the tool's specific resource and scope unambiguous. It distinguishes itself from sibling search tools like datasets_apps_search and datasets_apps_reviews_search by naming the exact dataset and its document model. This is a precise, verb-first statement with no vagueness.

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 description gives clear practical context: it explains the default behavior with no date ('latest snapshot is returned') and the recipe for rank history ('pair app_id with sort=date_desc'). It also enumerates valid enum values for store, chart_type, platform, and sort, helping the agent choose correct filter values. However, it never names alternative tools or explicitly states when not to use this tool, so it stops short of full exclusion guidance.

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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