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ai-vision-mcp

ai-vision-mcp

by tan-yong-sheng
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
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Audit Design

audit_design

Audits design compliance using pixel-level color, edge, and contrast analysis, enhanced by Vision Language Model critique.

Instructions

Perform design compliance auditing with pixel-level analysis (K-means colors, Sobel edges, WCAG contrast) and the critique of Vision Language Model.

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": {
      "imageSource": "<imageSource>"
    },
    "name": "audit_design"
  }
}

Input Schema

NameRequiredDescriptionDefault
promptNoOptional custom audit prompt to supplement the default design audit criteria
optionsNo
imageSourceYesImage source - can be a URL, base64 data (data:image/...), or local file path

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.0.7

TDQS

B3.3/5.0
Behavior3/5

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

The description discloses the algorithms used (K-means, Sobel, WCAG) and involvement of a Vision Language Model, which provides insight into behavior. However, without annotations, it lacks details on side effects, return format, or whether it is read-only. No output schema forces reliance on description for behavioral context.

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 sentence that efficiently conveys core behavior and techniques. While very concise, it omits important details, but the sentence itself is well-structured 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?

Given the complexity (nested options, 3 params, no output schema), the description is insufficient. It does not explain the output format, how to use imageSource, or what a successful audit returns. The lack of output schema increases the burden on the description, which is not met.

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?

Schema description coverage is 67%, so much parameter meaning is already conveyed. The description adds marginal value by noting the prompt is optional and custom, but does not elaborate on how options (topK, etc.) affect the audit. The nested options are not explained in the tool description.

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?

The description clearly states the tool performs design compliance auditing with specific techniques (K-means colors, Sobel edges, WCAG contrast) and VLM critique. It distinguishes itself from siblings like analyze_image and detect_objects by focusing on design compliance auditing.

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?

No explicit guidance on when to use this tool versus siblings (analyze_image, compare_images, etc.). It does not mention prerequisites, when not to use it, or alternative tools for different scenarios.

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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