label_add_batch

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

There are no annotations, so the description carries the full behavioral disclosure burden. It only states that labels are added and lists the label shape; it does not mention side effects, whether labels are appended or replace existing ones, what label track is targeted, or any validation behavior.

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 extremely concise and front-loaded with the core purpose. The Args section adds the essential parameter detail without unnecessary prose, making it easy to scan and parse.

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 no output schema and no annotations, the description is not complete enough for confident invocation. It omits the coordinate system, target label track, interaction with existing labels, return value, and any restrictions on label ranges, which are significant contextual gaps for a write operation.

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 input schema is nearly empty, with labels as an array of objects and additionalProperties allowed. The description compensates by specifying the exact expected object shape: start (float), end (float), and optional text (str). It does not clarify the meaning of start/end coordinates or units, but the core parameter semantics are clearly provided.

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 adds multiple labels in one call, identifying both the verb and the resource. It implicitly differentiates from the sibling label_add by emphasizing the batch aspect, though it does not explicitly compare against label_import or other label-related tools.

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 phrase 'in one call' implies this tool is for adding multiple labels at once, which offers some usage context. However, it does not explicitly state when to choose this over label_add, label_import, or other label tools, leaving the decision largely to inference.

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