label_join_regions

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

No annotations are present, so the description carries the transparency burden. It discloses meaningful behavioral details: order does not matter, labels stay put, and the operation is the inverse of label_split_regions. It does not state whether the operation is destructive or what the return value is, but the core behavior is clearly conveyed.

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 three terse sentences with zero filler. The primary action is front-loaded, and the clarifying behavioral notes are short and directly useful.

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 zero-parameter operation with no output schema, the description covers the essential context: what it does, how it relates to label_split_regions, and key invariants like labels staying put. It is complete enough for an agent to invoke it correctly without ambiguity.

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 tool has zero parameters and the schema is empty, so there is nothing for the description to explain about parameters. The baseline for a zero-parameter tool is 4, and the description appropriately avoids inventing parameter details.

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 states a specific action: joining audio clips across every labeled region, and explicitly identifies itself as the inverse of label_split_regions. This clearly distinguishes it from sibling label operations like label_cut_regions or edit_join without needing to inspect schemas.

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 gives clear usage direction by naming label_split_regions as its counterpart, implying it should be used to reverse or undo a split operation. It does not exhaustively list when not to use it, but for a zero-parameter command this is sufficient context.

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