Searchwire

Keywords an app ranks for

app_keywords

Read-only

The keywords an app ranks for in App Store or Google Play search, each with monthly store search volume and the app's rank (United States, English). $0.02 a call plus $0.0002 a keyword.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "app_id": "<app_id>"
    },
    "name": "app_keywords"
  }
}

Input Schema

Name	Required	Description
`limit`	No	Default 100.
`order`	No	"volume" highest first (default) or "rank" best first.
`store`	No	"apple" (App Store, default) or "google" (Google Play).
`app_id`	Yes	The number in an App Store link (e.g. "964220645"), or with store "google" the package name (e.g. "org.telegram.messenger").
`offset`	No
`max_rank`	No	Only keywords where the app ranks this high or higher.
`min_volume`	No

Schema Changelog

Changes observed during successful MCP inspections.

First observedOct 13, 2026

TDQS

A4/5.0

Behavior4/5

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

Annotations already declare readOnlyHint, openWorldHint, and destructiveHint=false, so safety is covered. The description adds genuinely useful context beyond that: the data is scoped to United States/English, and the tool is metered at $0.02 a call plus $0.0002 per keyword, which matters for agent decision-making on costly calls.

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?

A single, front-loaded sentence that names the resource, its scope, the return fields, and pricing, with no filler. Every clause earns its place.

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?

With no output schema and 7 parameters, the description does well to state the returned fields, geographic/language scope, and cost, letting the schema handle parameter mechanics. It stops short of explaining pagination or ordering behavior across large result sets, a minor gap for a paged list tool.

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 71%, so most parameters (app_id formats, store, order, limit) are already documented in the schema. The description only implies the volume/rank concepts and the US/English scope, adding little parameter meaning beyond the structured fields; baseline 3 is appropriate.

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: the keywords an app ranks for in App Store or Google Play search, plus what each result carries (monthly search volume and the app's rank). It is clearly distinguishable from siblings like app_keyword_volume or keyword_volume, which do not tie keywords to a specific app's rankings.

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

Usage Guidelines3/5

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

The description implies its use case (inspect the keywords a given app ranks for) and the required app_id, but it names no alternatives and gives no when-to-use vs. when-not guidance against siblings such as app_keyword_volume or app_search. Usage is inferable but not 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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