add_linear_pattern

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It does disclose that the tool returns mass properties and that feature_name defaults to the most recently added feature, which is useful. However, it does not mention that the operation modifies the part, what happens on invalid feature names, or any potential side effects, leaving gaps in transparency.

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 compact and efficient: a one-sentence purpose statement followed by parameter details. It front-loads the core operation and every sentence contributes useful information—no filler, digressions, or redundant repetition of the tool name.

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 4 parameters, no annotations, and no output schema, the description covers all parameters and explicitly states the return value (mass properties). It is largely sufficient for an agent to call the tool correctly. However, it omits explicit statements about model mutation and failure conditions when no feature exists, which would be valuable for full completeness.

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 0%, so the description is the sole source of parameter meaning. It explains all four parameters: count (times), spacing_mm (distance apart), direction (with examples like '+x'/'-x'+y'), and feature_name (with default behavior). This adds substantial semantic value beyond the bare schema, making correct invocation feasible.

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 a specific operation: 'Repeat a feature `count` times, `spacing_mm` apart, along a direction.' It names the resource (feature) and key parameters (count, spacing, direction). The linear nature and direction format (+x/-x/+y) implicitly distinguish it from the sibling add_circular_pattern, making the tool's purpose unambiguous.

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 provides parameter usage hints (direction format, feature_name defaulting to most recently added feature) but does not explicitly state when to use this tool versus alternatives like add_circular_pattern. It lacks any exclusions, prerequisites, or guidance on when not to use it, leaving the agent to infer usage from the name and context.

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