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get_dac_ur

View your DAC usage report: a detailed breakdown of spending by service, period, and transaction type. Useful for budgeting and trajectory analysis.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
toNoEnd date (ISO 8601)
fromNoStart date (ISO 8601)
auth_tokenNoYour DA agent auth token. Optional when this connection already carries one (Authorization: Bearer header on the remote server, or DA_AUTH_TOKEN for a local stdio server); an explicit value takes precedence.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • changedInput schema / properties / auth_token / description
      Previous value: -"Your DA agent auth token"New value: +"Your DA agent auth token. Optional when this connection already carries one (Authorization: Bearer header on the remote server, or DA_AUTH_TOKEN for a local stdio server); an explicit value takes precedence."
    • removedInput schema / required
      Removed value: -[
      -  "auth_token"
      -]
  2. First observed

TDQS

A3.6/5.0
Behavior2/5

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

No annotations are provided, so the description carries full responsibility for behavioral disclosure. It uses 'View' which implies read-only, but it does not explicitly state that no data is modified, whether authentication is required beyond the token parameter, or any other behavioral traits. The description is too sparse to fully disclose behavior.

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 two sentences with no wasted words. The core purpose is front-loaded, and the second sentence adds relevant context. Every phrase 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?

There is no output schema, so the description partially compensates by describing the report contents ('breakdown of spending by service, period, and transaction type'). However, it does not mention the return format, pagination, or any default behaviors. Given the tool's simplicity, this is fairly complete but not exhaustive.

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 the baseline is 3. The description does not add meaning beyond what the schema already provides; it mentions 'period' but does not elaborate on the 'from'/'to' parameters or any date format specifics.

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 verb ('View') and resource ('your DAC usage report'), and further specifies the report's content ('breakdown of spending by service, period, and transaction type'). This clearly distinguishes it from siblings like get_dac_balance, which likely returns a simple balance rather than a detailed report.

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?

The description gives an implied use case ('Useful for budgeting and trajectory analysis') but does not explicitly state when to use this tool versus alternatives, nor does it mention conditions or exclusions. Some context is provided, but the guidance is not robust.

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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