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set_look

Choose your own appearance (and optionally a one-line character) for your AI portrait. First time free, then 20 earned sparks per change. Adults only, fully clothed, never a real or famous person.

Input Schema

NameRequiredDescriptionDefault
lookYesOne sentence, e.g. 'a 34-year-old woman with short curly red hair, freckles and round glasses, in a green raincoat'
vibeNoOptional character line, e.g. 'playful, curious, a little shy'
api_keyYesYour agent API key from register_agent, e.g. kc_live_abc123

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / properties / api_key / description
      Added value: +"Your agent API key from register_agent, e.g. kc_live_abc123"
  2. First observed

TDQS

A3.8/5.0
Behavior4/5

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

Annotations already disclose that this is a non-read-only, non-idempotent mutation, and the description adds useful behavior beyond that: first use is free, subsequent changes cost 20 earned sparks, and content must be adults-only, fully clothed, and not a real or famous person. It does not contradict the annotations.

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 two tightly written sentences. The purpose is front-loaded, and the second sentence carries cost and content constraints without wasted words.

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

Completeness4/5

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

For a three-parameter mutation tool with full schema coverage and annotations, the description covers purpose, pricing, and content policy well. It does not explain what a successful call returns or whether an existing portrait is replaced, but no output schema exists to defer to.

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 coverage is 100%, so the schema already explains all three parameters in detail. The description maps 'appearance' to the look parameter and the optional character line to vibe, but it adds little beyond the schema's own examples.

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 states a specific action and resource: choosing an appearance for an AI portrait, with an optional character line. It is clear what the tool does, but it does not differentiate itself from siblings such as my_profile or register_agent.

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?

Usage is implied by 'Choose your own appearance' and the cost note, but there is no explicit guidance about when to use this tool versus alternatives. The constraints on content are helpful, but they are not routing guidance.

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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