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AppmanAi

by com.appmanai
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Keywords an app's competitors rank for

keyword_app_competitors
Read-only

List keywords that the competitors of one app rank for, with their popularity (SAP) and that app's own rank where it has one. Use it to find the gaps — keywords rivals own and this app does not. keyword_app_suggestions covers what the app itself already ranks for. Costs 6 credits.

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": {
      "store": "<store>",
      "country": "<country>",
      "package": "<package>"
    },
    "name": "keyword_app_competitors"
  }
}

Input Schema

NameRequiredDescriptionDefault
limitNoHow many rows to return, up to 200.
storeYesWhich app store: "android" (Google Play) or "ios" (App Store).
countryYesTwo-letter ISO country code, e.g. "US", "GB", "DE".
packageYesApp package / bundle id, e.g. "com.discord" (Android) or a numeric App Store id. If you only have the app name, call app_search first to resolve it.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint and openWorldHint, and the description adds genuinely new operational context: a concrete cost of 6 credits, which matters for an agent deciding whether to call it. It also discloses the shape of what comes back (SAP per keyword, the app's own rank only where it exists). It does not say how the competitor set is determined or whether results are ordered, which keeps it from a 5.

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?

Three short sentences: what it returns, what it is for, and the contrasting sibling, with the cost stated last as a cheap-to-scan footnote. No sentence repeats the schema or the title.

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, the description carries the burden of explaining returns, and it does name the key fields (keyword, SAP, own rank). The remaining gap is the undefined 'competitors' concept and result ordering, which an agent cannot infer from any structured field.

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 coverage is 100%, so all four parameters (limit, store, country, package) are already documented, including the instruction to call app_search to resolve a package id. The description adds no parameter-level meaning beyond the schema; its details are about return values, so the baseline of 3 applies.

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 and resource ('List keywords that the competitors of one app rank for') and names the exact contents of each row (SAP popularity plus the app's own rank). It explicitly differentiates itself from keyword_app_suggestions, so an agent can pick between them 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?

Gives an explicit use case ('find the gaps — keywords rivals own and this app does not') and names the alternative tool with the condition that selects it ('keyword_app_suggestions covers what the app itself already ranks for'). Nothing about when to prefer this is left to inference.

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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