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

readOnlyHint=true already tells the agent this is a safe read, and the output schema covers return shape, so the bar is lower; the description still adds meaningful scope ('logical workspace', covering both notes and drawn shapes) rather than just notes. It omits anything about ordering, counts, or whether the result spans multiple workspaces.

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?

One front-loaded sentence carries the substance, and the examples are short. The example block is somewhat padded for a zero-argument tool, but each line does illustrate a distinct retrieval intent (browse vs. lookup by label).

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?

With an output schema, zero parameters, and a readOnly annotation, almost everything an agent needs is already structured. The description is complete enough to invoke correctly; minor omissions about result ordering or cross-workspace scope are not blocking.

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 takes zero parameters, so there is nothing for the description to disambiguate; baseline 4 applies. The description correctly signals a parameter-free call by not implying any filtering arguments.

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?

Specific verb+resource ('List the notes and drawn shapes') with explicit scope ('on the logical workspace') and the fields returned (ids, positions, note text). The read-oriented verb naturally contrasts with the write siblings add_text_note, add_line_annotation, edit_text_note and delete_annotation.

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 two example queries ('What notes are on my topology?', 'Find the label that says LAN A') give clear situational context for when to call it. It stops short of naming an explicit alternative or stating when not to use it, so it is context-clear rather than fully prescriptive.

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