Update workspace brand settings. The designSpec field is a Markdown DESIGN.md document fed into AI generation system prompts — use it to encode voice, do/don't lists, and visual rules.
| Name | Required | Description | Default |
|---|---|---|---|
| apiKey | No | Send16 API key (overrides SEND16_API_KEY env var) | |
| logoUrl | No | ||
| designSpec | No | Markdown DESIGN.md spec for AI generation | |
| fontFamily | No | Body font family | |
| primaryColor | No | Hex color (e.g. '#4F46E5') | |
| secondaryColor | No | Hex color |
Changes observed during successful MCP inspections.
Input schema / properties / fontFamily / descriptionAdded value: +"Body font family"Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden of behavioral disclosure. It adds a useful behavioral detail about designSpec being fed into AI generation prompts, but does not disclose whether updates are partial or full overwrites, permissions required, or side effects. This is a moderate gap for a mutation tool.
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 sentences, front-loaded with the primary purpose, and the second sentence adds valuable detail about the designSpec field without any filler. Every word earns its place.
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?
Given the tool has 6 parameters, no required fields, and no output schema, the description covers the most important parameter (designSpec) but omits other behavioral context such as update semantics (partial vs. full) and authentication requirements. It is adequate for a simple update tool but has noticeable gaps.
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?
Schema coverage is high (83%), so the baseline is 3. The description enhances the designSpec parameter by explaining its role in encoding voice, do/don't lists, and visual rules, which goes beyond the schema's brief description. Other parameters are not elaborated, but the schema already covers them adequately.
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 clear action ('Update') and resource ('workspace brand settings'), which is specific and distinct from sibling tools like get_brand or update_campaign. The added detail about designSpec further clarifies the tool's unique purpose in managing AI generation prompts.
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?
The description provides clear context for when to use this tool (to update brand settings) and implicitly distinguishes it from read-only 'get' tools and other 'update_' tools. However, it does not explicitly mention when not to use it or mention alternatives, so it falls short of a 5.
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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