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

Beyond the annotations (readOnlyHint, idempotentHint), the description adds critical interpretation guidance: 'A missing year means not yet read — never read it as clean' and clarifies that only factual data is returned, no recommendations. This adds value beyond the structured metadata.

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 concise, with two sentences that pack the core function, usage context, a crucial caveat, and a factual-data disclaimer. Every sentence earns its place, and the structure is 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 single-parameter read-only tool, the description covers what it returns, how to interpret missing data, and its factual scope. It lacks explicit output schema but the caveats and page-cited detail make it adequately complete for an agent to call correctly.

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 schema already provides a complete description for the 'company' parameter (slug, symbol, or UUID), covering 100% of the schema. The description does not add extra parameter semantics, so baseline 3 is appropriate.

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 retrieves auditor opinions, key audit matters, CARO exceptions, and auditor changes per fiscal year, sourced from annual reports. This is specific enough to distinguish it from general company data tools, though it doesn't explicitly name sibling alternatives.

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 advises use for governance and red-flag questions, giving context on when to apply the tool. However, it does not mention alternatives or provide explicit exclusions, so the guidance is implied rather than directly contrasted with siblings.

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