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npu-vision-fallback

npu-vision-fallback

by Byte-Naut
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

ocr_region

Extract text from a specified screen region using NPU-accelerated OCR, or capture the full screen if no region is given.

Instructions

OCR a screen region. region=[x1,y1,x2,y2] in screen coords; omit for full screen.

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": "ocr_region"
  }
}

Input Schema

NameRequiredDescriptionDefault
regionNo[x1, y1, x2, y2]
backendNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

B3.4/5.0
Behavior2/5

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

No annotations provided, so description carries full burden. It only states the action and parameter format, but omits behavioral traits such as accuracy, performance, supported image formats, or what happens with invalid input.

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 with no unnecessary words. All information is relevant and front-loaded.

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?

Despite no output schema and no annotations, the description fails to explain return values, error handling, or how to select backends (refer to sibling tool list_backends but no mention). Simple but incomplete.

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?

Adds meaning for the 'region' parameter beyond schema (syntax 'region=[x1,y1,x2,y2]' and default behavior when omitted). However, the 'backend' parameter (50% coverage) lacks any description or guidance, so only partial compensation.

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?

Clearly states it performs OCR on a screen region, specifies the region format, and distinguishes from sibling tools by focusing on OCR rather than general analysis or UI detection.

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?

Implies usage for OCR on a region or full screen, but does not provide explicit guidance on when to use this vs alternatives like analyze_screen or detect_ui. No mention of prerequisites or exclusions.

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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