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Nanites

Nanites

by ADn-001
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Hybrid

Download Model

download_model

Retrieve a model from Hugging Face by source ID, with optional quantization, through the active LM Studio endpoint.

Instructions

Ask the active profile's LM Studio endpoint to download a model by HF source id, optionally pinned to a quantization.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "source": "<source>"
    },
    "name": "download_model"
  }
}

Input Schema

NameRequiredDescriptionDefault
sourceYes
quantizationNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

C2.8/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. The description mentions it asks the endpoint to download, but does not specify whether the download is asynchronous, whether it waits for completion, or what happens if the download fails. It also doesn't disclose rate limits, auth requirements, or potential side effects like populating the model registry. The verb 'download' implies a state-changing operation, but without annotations, this is a significant gap.

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 description is a single, concise sentence that front-loads the core action and key parameters. There is no wasted wording; it efficiently conveys the tool's purpose. It earns its place by providing enough detail to understand the basic operation.

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?

Given the tool's complexity (2 parameters, 0% schema coverage), the description is insufficient. It lacks detail on the return behavior (e.g., does it return a status?), whether the download is blocking, and how it relates to other download variants. With no output schema and no annotations, the description does not fully equip an agent to handle errors or interpret results, leaving an agent to infer too much.

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?

The schema coverage is 0%, with two parameters that have no descriptions. The description explains the 'source' parameter as an HF source id and 'quantization' as a pinning option, but it does not clarify the format of the HF source id (e.g., whether it includes the repo id or a full URL), nor does it specify acceptable values for quantization (e.g., 'q4_K_M' vs 'int4'). This leaves important semantics undocumented beyond the basic purpose.

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 clearly states the verb 'download' and the resource 'model by HF source id', with a specific optional parameter 'quantization'. It distinguishes itself from sibling tools like 'download_and_wait' and 'download_and_test' by specifying it is asking the active profile's LM Studio endpoint, rather than downloading and then waiting or testing. However, it does not explicitly differentiate from these siblings or mention alternative tools for downloading with different workflows.

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?

The description implies usage context: it says 'Ask the active profile's LM Studio endpoint to download', which indicates it operates on the active profile, but it does not clarify when to use this tool versus alternatives like 'download_and_wait' or 'download_and_test'. It lacks explicit guidance on when to use this tool versus waiting for completion or testing, and does not mention prerequisites like whether the model must be available or if a profile must be active.

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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