remove_text

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

Beyond the destructiveHint annotation, the description discloses critical behavioral details: it warns that without filters it removes ALL texts with matching content, and specifies the 0.1mm positional tolerance. This is exactly the kind of context that helps an agent understand the tool's destructiveness and matching logic.

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 well-structured: a one-sentence purpose, a behavior explanation with conditional logic, and a concise Args list. Every sentence adds value, and the most important information (remove all vs filtered) is 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?

For a tool with 4 parameters and conditional behavior, the description covers all parameters, the positional filtering logic, and the optional default for schematic_path. An output schema exists, so return values need not be described, and the description is sufficient for an agent to invoke the tool safely and correctly.

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?

The schema has 0% description coverage, but the description's Args section explains each parameter: text is the content to match, x/y are optional position filters, and schematic_path is the path with a default. It also adds the positional tolerance in the prose, providing meaning beyond the schema's bare types and defaults.

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's action: 'Remove text annotation(s) by content, optionally filtered by position.' This uses a specific verb and resource, and distinguishes it from sibling tools like remove_label by targeting 'text annotations' specifically. It also explains the conditional filtering behavior, making the 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 clear context on when to use the tool: it can either remove all texts with matching content or only those matching both content and position. However, it does not explicitly mention alternatives or when not to use it (e.g., for labels use remove_label), so it falls short of a 5 but is still well above minimal.

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