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Python
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vram_usage

Read-only

Check total VRAM used by loaded models and flag any over a set budget. Set a budget in bytes to detect over-budget models.

Instructions

[READ] Total VRAM used by loaded models; flag over-budget.

Args: budget_bytes: Optional VRAM budget; models over it are flagged. target: Ollama target name from config; omit for the default.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "vram_usage"
  }
}

Input Schema

NameRequiredDescriptionDefault
targetNo
budget_bytesNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.6.0

TDQS

B3.4/5.0
Behavior3/5

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

The [READ] prefix is consistent with readOnlyHint=true and adds no contradiction. Beyond the annotation, the description discloses one useful behavioral trait: models exceeding a supplied budget are flagged. It says nothing about output format beyond that flag or about cost/latency of the call.

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?

Front-loaded summary sentence followed by a compact Args block; each line carries information. The [READ] tag slightly duplicates the readOnlyHint annotation but is cheap and useful for scanning.

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?

For a simple two-parameter read tool with no output schema, the description covers the operation, both parameters, and the one non-obvious output behavior (over-budget flagging). Missing only return-shape detail and sibling routing, which are minor here.

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?

Schema description coverage is 0%, so the description must compensate, and it does document both parameters: budget_bytes as an optional VRAM budget with over-budget flagging behavior, and target as an Ollama config name that defaults when omitted. Only the byte unit/format of budget_bytes is left implicit.

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?

Names a specific verb-like operation and resource: reports total VRAM consumed by loaded models and flags models over budget. It is clearly distinguishable from siblings like server_status or running_models, though it never explicitly contrasts itself with them.

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 statement of when to reach for this tool versus alternatives (e.g. running_models or server_status), and no prerequisites or exclusions. The only usage-like guidance is 'omit for the default' on the target parameter, which is parameter-level rather than tool-selection guidance.

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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