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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false, and a closed world, so safety is covered. The description adds content semantics and the newest-first ordering, but says nothing about pagination, result size, or empty/absent notes, so it adds only modestly beyond the structured fields.

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?

Two compact sentences with no redundancy, and the subject (the notes) is front-loaded. The phrasing is slightly indirect and literary, but nothing is wasted.

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 read-only, no-output-schema tool with fully documented parameters and annotations covering its safety profile, the description communicates enough to call it correctly. It falls short of 5 only because sibling differentiation and usage conditions are not spelled out.

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?

Schema description coverage is 100%, so all three parameters (workbook, context, llm_model) are already documented in the schema. The description adds no parameter-level detail, so the baseline of 3 applies.

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 names a specific resource (notes a workbook's runs have kept) and what it shows, with concrete content examples ('preferences, corrections, where things are'). It is clear what the tool returns, though it does not explicitly distinguish itself from siblings like read_workbook or get_trace, so it stays below a 5.

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 hints at usage context ('Runs read them; this shows them') by contrasting the internal consumer with the caller. However, it gives no explicit when-to-use, when-not-to-use, or named alternative among the many workbook siblings, leaving selection guidance implied.

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