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TypeScript
Remote

check_metadata

Read-only

Check draft app store listing text against Google Play and Apple App Store rules to catch length errors, policy warnings, and iOS keyword issues before submission.

Instructions

Check draft listing text against the stores' own rules, before spending a run measuring it. Per field: the length as the STORE counts it (UTF-16 code units, which is not what a character count gives you in most languages), the limit, what is left, and warnings[]. warnings[].level is "error" (the store would refuse this as it stands), "warning" (it costs you something, or a reviewer may object) or "info" (worth knowing, often counter-intuitive: emoji are allowed in a Google Play description but banned in the app name). warnings[].rule names the policy when one fired: "price", "ranking", "play-program", "call-to-action", "kids", "rival-platform", or null for a limit or formatting warning. THE TWO STORES ARE NOT SYMMETRICAL, and this is the most actionable thing the tool tells you: Google NAMES forbidden words and rejects, so the same term is an error there; Apple publishes no list and a reviewer decides, so it is a warning. A draft can be perfectly valid on one store and refused on the other. valid is false only when at least one field carries an ERROR: a draft can be valid and still carry warnings worth acting on, so read them. notes[] carries anything wrong with the request itself, such as sending a keywords field to Google Play, which has none. On the iOS keywords field it also returns keywords{terms, duplicates, too_short, phrases, wasted_on_spaces, wasted_on_duplicates}: phrases are multi-word entries, which Apple splits apart and recombines itself, so they gain nothing over their words. It is pure arithmetic over the text you pass, with no store lookup, so it answers instantly: run it on every draft you write, in a loop if that helps, and call simulate_metadata only once it comes back valid.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
storeYesApp store: GPLAY (Google Play) or ITUNES (App Store)
titleNoApp name
kw_fieldNoiOS keywords field, comma separated. Google Play has no such field.
subtitleNoThe subtitle on iOS, the short description on Google Play
descriptionNoThe full/long description

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.5.0

TDQS

A4.6/5.0
Behavior4/5

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

Annotations already establish readOnlyHint=true, but the description adds substantial context: pure arithmetic over the passed text, no store lookup, answers instantly, and the semantic meaning of each warnings[].level and warnings[].rule. It also discloses the asymmetry between Google (errors) and Apple (warnings) and that valid=false only on errors. It stops short of stating rate limits or pagination, but for a stateless pure-function tool that is minor.

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?

It is a long, dense block, but it is front-loaded with the core purpose and most sentences earn their place by documenting return semantics that have no output schema. The emoji parenthetical and the keyword-field enumeration are slightly over-elaborated for the selection decision.

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

Completeness5/5

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

With no output schema, the description carries the full burden of explaining the return shape, and it does so thoroughly: per-field length/limit/remaining, warnings[].level with all three values, warnings[].rule with its enumerated policies, notes[], and the keywords object fields. An agent knows exactly what it gets back and how to act on it.

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; the description still adds meaning by clarifying the kw_field/store interaction ('sending a keywords field to Google Play, which has none') and distinguishing subtitle semantics across stores. Marginal but genuine value beyond 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 opens with a specific verb+resource ('Check draft listing text against the stores' own rules') and immediately scopes it against the sibling that follows ('before spending a run measuring it'). An agent can distinguish it from simulate_metadata without opening either schema.

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

Usage Guidelines5/5

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

It gives explicit usage guidance: 'run it on every draft you write, in a loop if that helps, and call simulate_metadata only once it comes back valid.' The alternative and the condition that selects it are both stated.

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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