Update brand fields

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

Since all annotations are false, the description carries the full burden of behavioral disclosure. It explicitly says 'Patch SPECIFIC fields ... WITHOUT overwriting the rest — a read-modify-write on the saved brand', which clearly reveals the partial-update behavior. This is strong transparency, though it does not disclose idempotency or error handling.

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 concise and well-structured: a main action sentence, two usage examples, and a pointer to an alternative tool. It is front-loaded with the critical behavior (patch without overwrite) and contains no redundant information.

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?

The description explains the patching behavior and provides usage examples, but it does not specify which brand is being updated (implicitly the current workspace brand, given sibling tools like list_brands and use_brand). It also does not mention any return value or error behavior, and there is no output schema. These gaps leave the invocation context incomplete.

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 description lists all 10 patchable fields, which helps the agent know what can be updated, and adds the practical instruction 'Only pass the fields you're changing'. However, with only 60% schema coverage, it does not compensate for the four undocumented parameters (name, audience, category, positioning) by providing semantic explanations; it merely names them.

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 clearly states the tool patches specific fields of the workspace brand profile without overwriting the rest, and lists the fields in parentheses. However, it does not differentiate itself from the sibling 'change_voice', which could be a more specialized tool for voice changes, leaving some ambiguity for the agent to decide between them.

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 gives explicit usage examples ('change our voice to playful', 'we sell to dentists now') and points to 'draft_brand' for full onboarding, which is a clear alternative. It also instructs to pass only changed fields. It does not, however, mention other alternatives like 'change_voice', so the guidance is not fully comprehensive.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.