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Read-onlyIdempotent

Break down AI coding spend by sub-agent type: run counts, dominant model, average cost, read-only tool-call share, errored results, and requested-vs-actual model mismatches.

Instructions

Spend per sub-agent type: runs, the model it mostly used, average cost per run, the share of runs whose tool calls were all read-only, errored tool results, and runs where the requested model differed from the one actually used.

Input Schema

TableJSON Schema

Name	Required	Description
`since`	No	window: 7d, 30d, 90d, all, or a YYYY-MM-DD start date; default 30d
`source`	No	restrict to one tool: "claude-code" or "codex"; default both
`project`	No	restrict to one project directory, exact match, or a prefix if it ends with a path separator
`currency`	No	override the detected plan: "usd" reports as charged, "share" reports as a subscription's list-price equivalent

Output Schema

TableJSON Schema

Name	Required	Description
`plan`	Yes	"api" or "subscription", re-detected on every scan
`agents`	Yes
`currency`	Yes	"usd" when the figures were charged, "list_price_equivalent" when a subscription covered them and the figures are what the usage would have cost on the API
`scan_error`	No	why the most recent scan attempt failed, in which case the figures are from the last successful scan
`age_seconds`	Yes	seconds since that scan; the server rescans when a tool is called more than 60 seconds after the last attempt, or on refresh
`ingested_at`	Yes	RFC 3339 time of the last successful transcript scan; empty if none has succeeded yet
`plan_reason`	Yes	why that plan was chosen

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Sep 12, 2026

TDQS

B3.2/5.0

Behavior3/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and openWorldHint=false, covering the safety profile. The description adds useful context about the metrics returned, but does not discuss authentication, rate limits, or other operational behavior beyond what annotations provide.

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?

The description is a single sentence that front-loads the core subject ('Spend per sub-agent type') and lists metrics efficiently. It is slightly long but every clause contributes useful information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool has an output schema and annotations, and all parameters are documented in the schema. The description summarizes return values but omits usage context and sibling differentiation, which are gaps for an agent selecting among the many reporting tools.

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 schema already fully documents all four parameters. The description adds no additional parameter meaning, which is appropriate given the schema's completeness.

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 names a specific resource (sub-agent type) and enumerates the metrics reported (runs, model, average cost, read-only share, errors, model mismatch). The purpose is clear, but it lacks an explicit verb and does not distinguish itself from sibling tools like report or prices.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no guidance on when to use this tool versus alternatives, no mention of prerequisites, and no exclusions. The description only lists output metrics, leaving the agent to infer context.

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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