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get_usage

Get usage metrics for the authenticated account. Shows verification counts, API calls, and quota usage.

ACCESS: needs a Proof account. Authenticate this client (Claude Code: /mcp → Authenticate), then call this tool again. start_login does NOT open this tool.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
monthsNoNumber of months of history
periodNoMonth to query in YYYY-MM format (e.g. 2026-01)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4/5.0
Behavior4/5

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

No annotations are provided, so the description carries the behavioral burden. It discloses that the tool operates on the authenticated account, lists the types of usage data returned, and states the authentication requirement. It does not discuss error cases or rate limits, but this is acceptable for a simple read-style tool.

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 is compact and front-loaded with purpose, then expands on returned metrics and access requirements. Every sentence adds useful information, and the ACCESS block is directly relevant to correct invocation.

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?

For a simple read-only metrics tool with only optional parameters and no output schema, the description provides sufficient context: what it returns, account scope, and authentication prerequisites. It could mention default behavior or interplay between months and period, but these are minor gaps.

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%, with both months and period already documented with types, constraints, and descriptions. The tool description adds no additional parameter semantics beyond what the schema provides, so a baseline score of 3 is appropriate.

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 clearly identifies the tool's purpose: retrieving usage metrics for the authenticated account, listing specific metric categories. It is specific enough to convey the resource and scope, but it does not explicitly differentiate itself from similar siblings like get_api_key_usage or get_platform_summary.

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?

The ACCESS block provides explicit context on when the tool can be used: the client must have a Proof account and be authenticated, with a note that start_login does not open this tool. It gives clear prerequisites but does not discuss when to prefer this tool over alternatives.

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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