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vom-core

storelift-mcp

get_change_impact

Read-onlyIdempotent

Compare app store metrics before and after a change day to measure its impact on keyword ranks, downloads, and subscription revenue.

Instructions

What a change did: for one change day (a new version, screenshots, subtitle, keyword field, a campaign start — defaults to the latest change on the listing timeline) compares the same number of days before and after, side by side: keyword ranks (up/down/entered/dropped and the biggest moves), the App Store funnel (impressions, page views, downloads per day and the conversion rates), downloads from the sales report, and subscription revenue and trial/paid starts per day, each with the change in percent. The change day itself is left out of both windows. complete=false means the after window is still running. recentChanges lists the last change days to pick another one.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dayNochange day YYYY-MM-DD (defaults to the latest change)
appIdYesapp id from list_apps
windowNodays on each side, 3–30 (default 7)
countryNocountry code for ranks and the listing timeline (defaults to the app's first country)

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.5.0

TDQS

A4.6/5.0
Behavior5/5

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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive, closed-world), and the description adds substantial non-obvious behavior: the change day is excluded from both windows, complete=false signals the after window is still running, and defaults are spelled out for day/window/country. These are exactly the traits an agent needs before invoking.

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?

Front-loaded with the core purpose and information-dense. However, it is one sprawling sentence with em-dashes and embedded lists that is harder to parse than necessary; a split into 2-3 sentences would read better without losing content.

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?

There is no output schema, so the description carries the return-value burden and does so thoroughly: it enumerates the metric families returned (rank moves, funnel counts and rates, downloads, subscription revenue/trial starts, each with percent change), plus the complete flag and recentChanges helper. Nothing needed to call or interpret it is missing.

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, but the description adds real meaning beyond the schema: 'window' means equal days on each side, the change day itself is omitted from the windows, and 'day' defaults to the latest change. It does not add format detail for country 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?

Opens with a specific verb+resource framing ('What a change did') and precisely defines the computation: comparing equal windows before and after a change day across keyword ranks, funnel, downloads, and revenue. This is clearly distinguishable from sibling reads like get_history, get_listing_timeline, or get_store_funnel.

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?

Usage context is clear: measure the impact of a specific change day, defaulting to the latest change, with recentChanges offering other candidate days. It does not explicitly state when to prefer an alternative sibling (e.g., get_history or get_listing_timeline), so it stops short of full routing guidance.

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