Skip to main content
Glama
vom-core

storelift-mcp

get_rivals

Read-onlyIdempotent

Identify rival apps ranking above yours in app store search. Get the keywords they beat you on, their rank (theirRank) and yours (ourRank); null ourRank means your app doesn't appear.

Instructions

Apps that rank ABOVE this app in search. For each rival you get the keywords it beats you on, its rank there (theirRank) and yours (ourRank) — ourRank null means the app does not appear for that keyword at all.

Input Schema

NameRequiredDescriptionDefault
appIdYesapp id from list_apps
countryNocountry code, e.g. tr, us (defaults to the app's first country)
platformNodefaults to ios

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv1.5.0
    • changedInput schema / properties / country / description
      Previous value: -"country code, e.g. tr, us"New value: +"country code, e.g. tr, us (defaults to the app's first country)"
  2. First observedv1.1.1

TDQS

A3.6/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, non-destructive and closed-world, so safety is covered. The description adds real behavioral context the annotations cannot: that each rival comes with the keywords it beats you on, the rival's rank and yours, and critically that a null ourRank means the app does not rank for that keyword at all.

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?

Two short sentences with zero filler; the core identity of the result set is front-loaded and the field explanations follow immediately. 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, the description must explain the return shape, and it does cover the main fields and the tricky null case. It stops short of describing pagination, ordering, or how many rivals are returned, which are minor residual gaps for this kind of read 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 100% (appId source, country code format, platform default), so the schema itself carries all parameter meaning. The description adds no parameter-level detail; its ourRank/theirRank remarks describe output, not inputs. Baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description names the resource precisely ('apps that rank ABOVE this app in search') and the verb is implied by the tool name, so an agent knows this returns competitor apps rather than managing them. It distinguishes itself from add_rivals/remove_rivals (mutations) by describing a read result, but never explicitly differentiates from the close sibling get_rival_detail.

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

Usage Guidelines2/5

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

There is no when-to-use guidance, no prerequisite (other than the schema's 'app id from list_apps'), and no mention of alternatives such as get_rival_detail or get_rival_market for deeper per-rival information. The agent must infer the use case purely from the stated return content.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.