label_object

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

With no annotations, the description must disclose behavioral traits. It mentions that the tool modifies an object by assigning a name, but it does not state whether it overwrites existing labels, requires special permissions, or has any side effects. The return type is specified, but overall transparency is moderate.

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, front-loaded with the purpose, and includes an organized list of parameters and examples. A bit more structure (e.g., separating examples) would improve readability, but it is already efficient.

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 the tool's simplicity, the description covers the basics: purpose, parameters, and return value. However, it lacks mention of prerequisites (e.g., connection to grandMA2) and does not explain whether labeling is immediate or requires further steps. The presence of an output schema (though not shown) is acknowledged via the return statement.

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% coverage, so the description adds significant value by listing parameter names with explanations and examples ('object_type: Object type (e.g., "group", "cue")'). This clarifies meaning beyond the bare schema types.

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 'Assign a name label to a grandMA2 object' with a specific verb and resource. It distinguishes itself from sibling tools like 'label_macro_tool' or 'label_sequence_cue' by being a general labeling tool for any object type.

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?

No guidance is provided on when to use this tool versus the many sibling labeling tools (e.g., label_cue_across_sequences, label_macro_tool). The examples illustrate typical usage but do not define selection criteria or alternatives.

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