remove_label

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

The description goes beyond destructiveHint=true by specifying that without positional filters ALL matching labels are removed and that matching uses 0.1mm tolerance. This discloses the actual destructive scope and avoids surprises. It does not contradict the 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?

The description is compact and logically structured: behavior first, then conditional rules, then a usage hint, then parameter definitions. No redundant sentences.

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?

For a destructive filter/removal tool, it covers the action, positional edge cases, an alternative for moving labels, and all parameter meanings. The output schema handles return values, so no additional return documentation is needed.

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 has 0% description coverage, but the Args section defines every parameter: text as match string, x/y as optional position filters, and schematic_path with default behavior. It adds semantics such as 'within 0.1mm tolerance' that the schema lacks.

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 uses a specific verb ('Remove') and names the exact resource ('net label(s) or global label(s) by text'), clearly differentiating it from sibling tools like remove_hierarchical_label. It also mentions optional position filtering, giving a precise scope.

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?

It explicitly describes conditional behavior: when x/y are provided, only matching labels within tolerance are removed; otherwise all matching-text labels are removed. It provides an alternative workflow for moving global labels via add_global_label, and the scope (net/global vs hierarchical) is evident.

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