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Download And Wait

download_and_wait

Starts an LM Studio model download from a Hugging Face source ID and polls status with exponential backoff until it completes, fails, or pauses.

Instructions

Workflow #4 download half: ask LM Studio to download a model by HF source id, then poll download status with exponential backoff until completed/failed/paused (or a poll ceiling).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sourceYes
profileYes
quantizationNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

B3.1/5.0
Behavior3/5

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

With no annotations, the description carries the full transparency burden. It usefully discloses the polling strategy, exponential backoff, terminal states, and poll ceiling, but it does not mention prerequisites like LM Studio being available, auth requirements, rate limits, or what the tool returns when it exits.

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 focused sentence with no fluff, and the core action is front-loaded. The only slightly opaque phrase is 'Workflow #4 download half,' but it does not significantly hurt readability.

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

Completeness2/5

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

For a tool with 3 undocumented parameters, no annotations, and no output schema, the description omits important context: what profile means, what quantization values are valid, what the return value is, and what the poll ceiling is. The description captures the workflow shape but not enough to call it reliably in all cases.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must explain all three parameters. It only clarifies that 'source' is a Hugging Face source id; 'profile' and 'quantization' are left unexplained, with no format, examples, or required-value context.

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 states a specific verb+resource: ask LM Studio to download a model by HF source id, then poll download status. It is clear enough to distinguish from siblings like download_model or get_download_status, though it does not name them explicitly.

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

Usage Guidelines3/5

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

The behavior 'then poll download status until completed/failed/paused' implies this tool is for callers who need to wait for a download outcome. However, it gives no explicit when-to-use guidance or alternatives, such as 'use download_model if you only want to start the download.'

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