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colab_usage

Check the account's compute-unit balance and current burn rate to monitor Colab credit consumption and prevent unexpected exhaustion.

Instructions

Show the account's compute-unit balance and current burn rate.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.5/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full burden; 'Show' implies a non-mutating read and it names exactly what is reported (balance and burn rate), which is the core behavior for a query tool. It says nothing about whether the read is live vs cached, whether units are shared across sessions, or whether the call itself has any cost, leaving meaningful gaps for a definition with zero annotation support.

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?

A single front-loaded sentence stating the resource and the two values returned, with no filler, hedging, or restated tool name. Every word 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?

An output schema exists, so the description need not explain return values, and with no parameters there is nothing else to document structurally. It is nearly complete, missing only the usage context that would help an agent decide between this and other status tools.

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?

The tool takes zero parameters, so per the rubric the baseline is 4 and there is no parameter semantics to compensate for. Schema description coverage is effectively 100% by vacuity.

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 verb+resource pair ('Show the account's compute-unit balance and current burn rate'), which is materially distinct from quota-free siblings like colab_status or colab_runtime_info. It never explicitly says how it differs from those adjacent status tools, so it lands at clear-but-undifferentiated rather than top-tier.

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 an agent should call this versus colab_status, colab_runtime_info, or colab_drive_status, all of which could plausibly be consulted for account state. The purpose implies a billing/quota-check use case but nothing states it, and no prerequisites or exclusions are given.

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