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appstore_list

Retrieve App Store collection rankings, including top free, paid, grossing, and new apps. Filter by country, category, and language, with optional full app details.

Instructions

Retrieve App Store collection rankings. Returns ranked App Store apps from an iTunes RSS collection, optionally expanded to full lookup details. collection enum: topfreeapplications, toppaidapplications, topgrossingapplications, topfreeipadapplications, toppaidipadapplications, topgrossingipadapplications, topmacapps, topfreemacapps, topgrossingmacapps, toppaidmacapps, newapplications, newfreeapplications, newpaidapplications. Of the Mac collections, only topfreemacapps currently returns ranked apps — topmacapps, topgrossingmacapps, and toppaidmacapps are accepted but Apple's feed for them is currently empty. There is no separate Games collection — combine any collection with category=6014 (or a Games subgenre ID, e.g. 7012 for Puzzle) to get its Games-only equivalent, e.g. Top Free Games. See the endpoint markdown for the full category ID table.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
numNoNumber of apps to return
langNoResult language tag
countryNoTwo-letter storefront country code
categoryNoNumeric App Store category ID, see description for the full enum; e.g. 6014 = Games, 7012 = Games/Puzzle
collectionNoChart collection slug, see description for the full enum
full_detailNoExpand each app via lookup API
Behavior5/5

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

With no annotations, the description carries full behavioral burden. It discloses that certain accepted collection values return empty results (Mac collections), explains the category workaround for Games, and mentions optional expansion via full_detail. This goes beyond the schema and anticipates common agent confusion, which is excellent transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is dense but every sentence earns its place. It front-loads the main purpose, then enumerates valid values, highlights known issues, and gives a category workaround. The structure moves from general to specific, and the length is justified by the amount of necessary information.

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?

Given 6 free-form parameters and no output schema, the description covers purpose, valid inputs, and behavioral quirks thoroughly. The main gap is that it does not describe the return structure beyond 'ranked apps', which could matter for an agent parsing results. However, it provides enough context for a list tool, and the endpoint markdown reference offers an escape hatch. Slightly more detail on the response format would make it complete.

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

Parameters5/5

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

Schema coverage is 100%, but the description adds substantial semantic value: it enumerates all collection values, notes which are currently broken, and explains how to use category for Games. This extra context is essential for parameter selection and is not fully captured by the schema descriptions alone. The description essentially acts as the reference for the collection enum.

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 states a specific verb and resource: 'Retrieve App Store collection rankings.' It clearly distinguishes from sibling tools like appstore_search and appstore_app by focusing on rankings from a collection. The scope is unambiguous and matches the tool name.

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?

Provides clear context on when to use the tool (for collection rankings) and includes critical usage caveats: which Mac collections work, how to simulate Games rankings via category. It does not explicitly name alternative tools for different use cases, but the purpose is clear enough that an agent can differentiate from siblings. The pointer to endpoint markdown for full category IDs also supports correct usage.

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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