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storelift-mcp

storelift-mcp

by vom-core
OverviewSchemaSourceRelated ServersDiscussions(1)Admin
JavaScript
Remote

draft_listing

Generate an app listing draft from measured keyword demand for one storefront, with title, subtitle, promo text, description, character counts, and review checks.

Instructions

A listing draft — title, subtitle, promotional text and description — built from the keywords measured for this app in one storefront, ordered by demand. Every field comes with its character count against the store limit, plus two review checks: an Apple product name in the title or subtitle (App Store only) and pricing language. termsUsed lists the measured terms behind it; excluded the tracked terms still to be measured. Nothing is written to the store — update_listing does that. Uses one AI writing credit (Pro and above).

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": {
      "appId": "<appId>"
    },
    "name": "draft_listing"
  }
}

Input Schema

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

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.5.0

TDQS

A4.3/5.0
Behavior4/5

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

The annotations only declare it is not read-only, not idempotent and not destructive; the description adds the substantive context behind those flags — that each call consumes one AI writing credit (Pro and above) and that no store state changes. It also discloses the two review checks and the App Store-only condition on the product-name check, which annotations cannot express.

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?

The description front-loads what the artifact is, then layers output contents, review checks, the sibling boundary and the credit cost in roughly three tight sentences. Every clause carries information an agent needs; nothing is restated from the name or schema.

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 correctly takes on the return-value burden: it enumerates the draft fields, the per-field character counts against store limits, the two review checks and the termsUsed/excluded arrays. Combined with the credit and non-persistence notes, an agent has everything required to call it correctly.

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%, so cc, appId and platform are already documented in the schema; the description reinforces 'one storefront' but adds no syntax, default behavior or format detail beyond that. Baseline 3 is the right score when the schema carries the parameter burden.

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 names a concrete artifact (a listing draft composed of title, subtitle, promotional text and description) and states the exact basis for it: keywords measured for this app in one storefront, ordered by demand. It is immediately distinguishable from update_listing, which it names as the tool that actually persists changes.

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?

"Nothing is written to the store — update_listing does that" gives an explicit boundary against the most confusable sibling, so an agent knows drafting is non-persistent and mutation requires a different call. It stops short of positioning against localize_listing or validate_listing, so the routing guidance is clear but not exhaustive.

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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