list_brandsLists all brand kits in your Canvora account, including names, colors, fonts, logos, and tone, so you can retrieve brand IDs and apply consistent styling to generated visuals.
List all brand kits in your Canvora account. Returns brand names, colors, fonts, logos, and tone. Use the brand ID with confirm_generation to apply brand styling.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already establish this as a safe, idempotent read operation. The description adds useful content detail by listing the returned brand attributes: names, colors, fonts, logos, and tone. It omits pagination or ordering behavior, but the tool has no parameters and the annotation set carries the safety profile.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two compact sentences with no filler. The core action is front-loaded, followed immediately by return contents and a downstream usage hint.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter list tool with no output schema, the description supplies exactly what an agent needs: what is listed, what fields are returned, and how the result is used with confirm_generation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool takes zero parameters, so there is no parameter semantics to explain. The description correctly does not invent parameter guidance and instead focuses on the returned data and downstream usage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb and resource: 'List all brand kits in your Canvora account.' It further distinguishes the tool by naming the sibling confirm_generation as the downstream consumer of brand IDs.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
It explains the practical use case: retrieve brand IDs to pass to confirm_generation for branded styling. It gives clear context but does not explicitly state when not to use this tool or name a competing alternative.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.