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Price My Usage

price_my_usage
Read-onlyIdempotent

Prices past coding agent usage from a ccusage or codeburn export or token mixes across rated models, showing what the same sessions would cost elsewhere.

Instructions

Price the user's own past coding agent usage, from a ccusage or codeburn export, on every rated model: each session at the price of its day, the models that keep the rating and cost less, a 95% range for the cost per session, and whether two models differ for real or the data cannot tell. Use when a usage export (or a list of token mixes) exists and the question is what the same work would have cost elsewhere. Not for a future workload (estimate_cost) or for a prompt (suggest_for_project). Reads token counts, names and dates only; nothing leaves the computer.

Input Schema

NameRequiredDescriptionDefault
mixNoInstead of a file: token mixes as {model, date, input, output, cache_read, cache_write, session?}
taskNoThe kind of work the sessions were (default: codeburn's categories, else coding)
limitNoHow many models to list in every_model (the cheapest first)
exportNoPath of a token export on this computer: `ccusage daily --json > f.json`, `ccusage session --json > f.json`, or `codeburn export -f json -o f.json`
compareNoTwo models to test against each other on the same sessions

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.22.0

TDQS

A4.7/5.0
Behavior5/5

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

Beyond the read-only and idempotent annotations, the description discloses the data scope ('Reads token counts, names and dates only') and privacy property ('nothing leaves the computer'). It also characterizes the analysis outputs, including per-session historical pricing, cheaper alternatives, a 95% range, and model-comparison significance.

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 definition is front-loaded with the core action, then adds use conditions, exclusions, and privacy context. Despite being a dense paragraph, every clause contributes relevant selection or behavioral information for a complex analysis tool.

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?

Given the presence of an output schema, full input-schema descriptions, and read-only annotations, the description supplies the remaining needed context: what the tool answers, when to choose it, when not to, and its local-only data handling. Nothing material is missing for correct invocation.

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 all five parameters are already documented in the input schema. The description adds domain context that inputs can come from a ccusage/codeburn export or token mixes, but it does not add parameter-specific detail for task, limit, or compare beyond the schema.

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 and resource: pricing the user's own past coding-agent usage from an export or token-mix list across every rated model. It also explicitly distinguishes this from sibling tools for future workloads (estimate_cost) and prompts (suggest_for_project).

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

Usage Guidelines5/5

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

It gives a clear use condition: when a usage export or token-mix list exists and the question is what the same work would have cost elsewhere. It also names when not to use it, routing the agent to estimate_cost and suggest_for_project.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.