Plan relevant design principles

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

Annotations indicate read-only, idempotent, non-destructive behavior, which is consistent with 'Select... Returns...' in the description. The description adds transparency by listing specific output elements (e.g., placement guidance, verification checks, relevance scores) and filtering capabilities, providing valuable context beyond annotations.

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 efficient sentences with no redundant language. The first sentence establishes the tool's purpose and scope, and the second covers filtering and output. Every word adds value.

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 complexity (6 parameters, no output schema), the description covers core functionality but omits details on limit and locale parameters, and does not specify behavior for edge cases like no results. Annotations provide safety context, but the description could be more thorough.

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 0%, so the description must compensate. It explains filtering by concerns, surface, phase, or ids (4 of 6 parameters), but fails to mention limit and locale parameters. This partial coverage adds some meaning but leaves gaps.

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 selects a small set of practical visual-design principles and details the output (placement guidance, application steps, etc.). It distinguishes from sibling tools like recommend_design_direction and get_ux_principle_plan by specifying the domain (visual-design) and output format.

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 implies usage through filtering options (concerns, surface, phase, ids) but does not explicitly state when to use this tool over alternatives like get_ux_principle_plan or compose_design_tokens. No guidance on prerequisites or exclusions is provided.

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