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

Annotations already declare readOnlyHint=false, destructiveHint=true and idempotentHint=false, so the safety profile is carried by structured data. The description adds useful output context (branded headers, smart number formatting, auto-fitted columns) but never explains the side effects implied by the annotations — what is written and where, whether repeated calls accumulate files, or why the operation is non-idempotent. That is a notable gap for a flagged non-read-only tool.

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?

Three short sentences, front-loaded with the core purpose and the sibling comparison before the cosmetic output details. Every sentence earns its place: purpose, differentiation, and output expectations, with no redundancy against the schema.

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?

There is no output schema, so the description does carry the burden of describing the return, and it does so reasonably (downloadable Excel file with branded formatting). However, it leaves the annotation-declared destructive/non-idempotent behavior unexplained, which is the one thing an agent most needs to know before invoking a flagged write-like tool.

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 both parameters (query, title) are already documented in the schema, including a title example. The description's only added signal is that 'query' is the same SQL used with stock_data_query, which points the agent at the sibling for query syntax but adds no format or constraint detail. Baseline 3 applies when the schema does the heavy lifting.

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 verb+resource ("Export query results to a branded Shibui Finance Excel spreadsheet") and explicitly distinguishes itself from the sibling stock_data_query ("returns a downloadable Excel file instead of raw data"). An agent can tell exactly what this does and how it differs from the raw-data tool without inspecting either schema.

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 clearly frames when this tool is appropriate versus the alternative: same SQL as stock_data_query, but returns a file rather than raw rows, which implies using it when a deliverable/spreadsheet is needed. It stops short of an explicit directive (e.g., "use this when the user asks for a downloadable/file deliverable rather than inline data") or any when-not guidance.

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