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

Annotations already declare a safe, closed-world read operation, so the bar is lower, and the description adds real context: output is a fixed thirteen-section scaffold, tone words resolve against a fixed lever table with conflicting pairs named and unknown words flagged, constraints are bucketed into seven categories, and identical input yields identical output. The only thing missing is guidance on limits (e.g. how many tone words are useful).

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?

Purpose and required parameter are front-loaded, and each subsequent sentence carries substantive information about outputs and processing. It is a single dense block, though, and the thirteen-section enumeration could have been a compact list for faster scanning.

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?

There is no output schema, so the description carries the full burden of describing the return value, and it does so thoroughly: the thirteen section names, what each contains (decided items, open decisions, blank fill-in lines), and how inputs are mapped into them. An agent has everything needed to decide to call it and to interpret the result.

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 description coverage is 100%, so the baseline is 3, but the description adds semantics the schema lacks — that name is required while audience/tone/constraints are optional, that tone accepts comma-separated text or a list, what example constraints look like ('must meet WCAG AA'), and crucially how tone and constraint values are processed downstream.

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?

States a specific verb and artifact ('Produce a deterministic brand guideline skeleton') and immediately enumerates the thirteen sections it returns. This is clearly distinguishable from sibling planners/linters like brand_architecture_planner (structure decisions) or lint_brand_voice (copy checking), because it explicitly says it generates templates and nothing more.

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 makes the tool's nature clear ('deterministic ... skeleton', 'nothing is generated beyond these templates'), which implies it is a starting scaffold rather than an analyzer. However it never states when to use this instead of siblings such as brand_architecture_planner or brand_voice_consistency, and gives no prerequisites or exclusions.

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