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storelift-mcp

storelift-mcp

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

get_usage

Read-onlyIdempotent

Check current workspace quota usage and reset times for tracked keywords, apps, AI features, spy, and API credits without spending credits.

Instructions

Every quota of the workspace with what is used and the reset time: tracked keywords, apps, discovery, AI questions, review AI, AI visibility, spy, API credits, today's Hive allowance and the per-second rate. Costs no credits. used=null means the quota is not metered on this plan, not zero.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "get_usage"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.5.0

TDQS

A4.3/5.0
Behavior5/5

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

Annotations already declare readOnly/idempotent/non-destructive, so the bar is lower, and the description clears it by adding two facts the structured fields cannot express: the call consumes no credits (contrasting with the many credit-consuming sibling tools) and the null-semantics of "used" (unmetered plan, not zero). These are exactly the behavioral details an agent needs to interpret the response correctly.

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?

Two tight sentences with the resource and its contents front-loaded, and the caveat about "used=null" placed last where it reads as a footnote. The quota enumeration is slightly long but every item is informational, so it largely earns its space.

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 carry the return-value burden, and it does so reasonably: it lists the quota categories and explains the reset time and the null case. It stops short of describing the exact response shape or field nesting, but for a zero-parameter read tool it is complete enough to call and interpret.

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?

There are zero input parameters, so the baseline is 4 and there is nothing for the description to disambiguate. No parameter-level explanation is needed or missing.

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 states a specific resource (workspace quotas) plus exactly what is returned: usage, reset time, and an enumeration of the quota categories (tracked keywords, apps, discovery, AI questions, API credits, Hive allowance, per-second rate). This is far more specific than the sibling read tools like whoami or get_today, and an agent can identify it without opening anything else.

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?

Usage is implied rather than stated: an agent infers you call this to check remaining quota/limits. The one explicit guideline, "Costs no credits," is genuinely useful for deciding whether to call it, but there is no when-not guidance or named alternative (and no obvious sibling overlap), leaving usage at an implied level.

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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