read_selection

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

Beyond the readOnly and idempotent annotations, the description discloses the empty-selection behavior (has_selection=False rather than an error), the API limitation about pitch and bar/beat position, and routes around that limitation. This gives the agent accurate expectations for edge cases.

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 with a clear purpose statement, a concise returns section, and a useful note about limitations. Every sentence contributes meaning, and the most important behavioral details are 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 zero-parameter read tool with an output schema and strong annotations, the description covers what the agent needs: what the tool reads, how to prepare the selection, what empty selections return, and where to go for unavailable data. Nothing essential is missing.

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, so parameter semantics are largely moot. The baseline for zero-parameter tools is 4, and the description correctly focuses on behavior and return values instead of 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 clearly states the tool reads rhythmic and notation properties of the active selection, and lists concrete properties like duration, dots, articulations, accidental, and event type. This distinguishes it from sibling tools that read full scores or project information.

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 tells the agent to establish the selection first, either in Dorico or via goto_bar, and warns that this tool cannot change the selection. It also names specific alternatives for reading pitch data, which is not available here.

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