brand_clarify

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

With no annotations, the description carries full burden. It reveals the tool is interactive, requires user answers, and returns updated identity and remaining clarification count. It does not mention destructive actions or permissions, but the behavioral traits are adequately disclosed.

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?

Two sentences, front-loaded with purpose, no wasted words. Structure is clear: what it does, when to use it, input format, and output.

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?

Despite no output schema, the description mentions returns (updated identity and remaining count). It ties the tool into the broader workflow (post brand_compile) and covers all needed details for a tool with only two parameters.

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 100%, baseline 3. The description adds value by explaining answer formats (hex, role, font, yes/no, natural language) with examples, going beyond the schema's brief descriptions.

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's purpose: resolving ambiguous brand values interactively. It specifies the context after brand_compile and gives concrete examples of ambiguous values (wrong primary color, unknown font). This distinguishes it from sibling tools like brand_compile and brand_check.

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 explicitly says 'After brand_compile', providing clear usage context. It implicitly guides when to use this tool (after compilation has identified ambiguities) but does not explicitly state when not to use it or suggest alternatives.

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