suggest_scale

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

No annotations are provided, so the description must disclose behavior. It states the tool 'suggests' parameters and combines multiple standards, implying a read-only recommendation. However, it does not mention side effects, authentication needs, or rate limits. It is moderately transparent but lacks detailed behavioral context.

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 with two sentences. The first sentence clearly states the action and purpose. The second sentence lists design standards, which adds value but could be streamlined. Overall, it is well-structured and front-loaded.

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 tool has 3 parameters all documented, but no output schema. The description hints at return fields ('strategy, ratio, base, constraints') but does not explicitly declare them. It also lacks differentiation from sibling tools like 'generate_scale'. The description is adequate but incomplete for full context.

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% with all parameters described in the schema. The description adds no extra meaning beyond the schema; it only mentions output fields ('strategy, ratio, base, constraints') which are not parameters. Thus, it meets the baseline for high schema coverage.

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 suggests optimal scale parameters based on design principles, with a verb (suggest) and resource (scale parameters). It lists several design standards, making the purpose specific. However, it does not explicitly distinguish from similar sibling tools like 'generate_scale', so it loses a point for sibling differentiation.

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 the tool is used when one wants scale parameters derived from design principles, but it provides no explicit guidance on when to use it versus alternatives (e.g., 'generate_scale') or when not to use it. The usage context is implied rather than stated.

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