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resource_usage_snapshot

Capture CPU, memory, disk, and GPU usage in Colab, optionally appending to a JSONL file.

Instructions

Captures CPU, memory, disk, and GPU usage through Colab Terminal and optionally appends it to a JSONL file.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
savePathNoRuntime path to append the JSON usage snapshot to. Set to an empty string to avoid saving./content/colab_mcp_usage.jsonl
Behavior3/5

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

Without annotations, the description should fully disclose behavior. It states what is captured and the optional file append, but does not mention read-only nature, performance impact, or any prerequisites. Basic transparency is present but lacks depth.

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?

Single sentence that clearly explains the action and optional saving. Front-loaded with the main purpose, no redundancy.

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?

Although it lists what is captured, the description omits the exact structure of the returned snapshot (e.g., keys, units). With no output schema, this leaves ambiguity about the data format. Adequate but not thorough.

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 coverage is 100% with the param description already explaining the savePath. The description adds no extra meaning beyond 'optionally appends it to a JSONL file,' so it meets the baseline without exceeding it.

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 clearly states the tool captures CPU, memory, disk, and GPU usage and optionally saves to a JSONL file. This distinguishes it from sibling tools like check_gpu (only GPU) or sample_gpu_usage (similar but limited to GPU).

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?

No guidance on when to use this tool over alternatives such as read_gpu_monitor or sample_gpu_usage. The description fails to mention scenarios where a full snapshot is preferred over a targeted check.

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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