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sketchy-mcp

sketchy-mcp

by ddkbs
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Local

Download model

download_model

Starts downloading a photo-labeling model for the model picker, letting users choose small, medium, or large tiers for local photo labeling.

Instructions

Start downloading a photo-labeling model. Used by the model picker.

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": {
      "tier": "<tier>"
    },
    "name": "download_model"
  }
}

Input Schema

NameRequiredDescriptionDefault
tierYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.8

TDQS

C2.6/5.0
Behavior2/5

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

With no annotations, the description carries the full burden. "Start downloading" implies an asynchronous operation, but it never says the call returns before completion, how to track progress (the model_status sibling goes unmentioned), whether repeated calls re-download, or what permissions or storage are required.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two short sentences with no filler, and the action is front-loaded. However, the second sentence spends space on a low-value implementation note ("used by the model picker") instead of information the agent needs.

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?

This is a no-annotation, no-output-schema, single-parameter tool whose behavior is inherently stateful (a background download). The description leaves out completion tracking, failure handling, and parameter meaning, so an agent cannot call it confidently in a workflow.

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% and the single required parameter 'tier' is only an enum of small/medium/large. The description says nothing about what the tiers mean in terms of model quality, size, or download time, so it fails to compensate for the schema gap.

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?

"Start downloading a photo-labeling model" gives a clear verb and resource, and the async "start" framing is meaningful. It does not explicitly distinguish itself from siblings like choose_model or model_status, but the action itself is unambiguous.

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 phrase "Used by the model picker" hints at the calling context but gives no when-to-use or when-not guidance, no relationship to choose_model or model_status, and no prerequisites. An agent must infer whether this follows or replaces model selection.

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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