mcp-face-transform

face_change_gender

Specify target gender per face and transform the portrait's facial gender appearance.

Instructions

Swap perceived facial gender characteristics in a portrait.

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": {
      "image_url": "<image_url>",
      "gender_infos": "<gender_infos>"
    },
    "name": "face_change_gender"
  }
}

Input Schema

Name	Required	Description	Default
`image_url`	Yes	URL of the portrait whose facial gender should be swapped.
`gender_infos`	Yes	Target gender information for each face, optionally including face_rect. Example: [{'gender': 1, 'face_rect': {'x': 0, 'y': 0, 'width': 100, 'height': 100}}].

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Aug 18, 2026

TDQS

B3.3/5.0

Behavior2/5

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

With no annotations provided, the description must fully disclose behavioral traits. It only states the transformation intent but does not mention whether the operation is destructive, requires authentication, returns an image URL, or processes multiple faces (though the gender_infos parameter suggests array support). The agent lacks critical 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.

Conciseness5/5

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

The description is a single sentence of 8 words, highly concise and front-loaded. Every word serves the purpose of defining the tool's function. No wasted or redundant language.

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

Completeness3/5

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

Given the tool has 2 parameters and an output schema, the description is incomplete. It does not mention that the tool can handle multiple faces in one call (implied by gender_infos array), nor does it describe the output format (though output schema exists). The description could be more informative without becoming overly verbose.

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 100%, so the baseline is 3. The tool description does not add any parameter-specific meaning beyond what the schema already provides (image_url and gender_infos with example). It meets the minimum threshold but adds no extra semantic value.

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 "Swap perceived facial gender characteristics in a portrait" uses a specific verb ('swap') and resource ('facial gender characteristics in a portrait'), clearly distinguishing this tool from siblings like face_change_age (age) and face_swap (face swapping). The purpose is unambiguous and directly conveys the tool's core function.

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 provides no guidance on when to use this tool versus its siblings (e.g., face_change_age, face_swap, face_beautify). It does not specify contexts, prerequisites, or alternatives. The agent must infer usage solely from the tool name and sibling tool names, which is insufficient for informed 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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