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

Annotations already declare readOnlyHint=true and destructiveHint=false, but the description adds substantial behavioral context: data comes from dimensional XBRL facts, source values are as-reported and never estimated, segment operating margin is derived, and rows can overlap (warning never to sum rows). This goes beyond annotations and helps the agent predict output quirks.

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 longer than average but every sentence carries information: purpose, data source, period/restatement rules, derivation method, overlap warning, and alternative tools. It is front-loaded with the main purpose and then details. Some jargon ('folded raw member QName') is dense but purposeful.

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 no output schema, the description must explain return structure, and it does: one table per axis, total row included, rows can overlap, and derived margin definition. It also covers data provenance, period constraints, and explicit alternatives. This is complete for an agent to invoke and interpret results 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?

Schema description coverage is 100%; the input schema already documents ticker and maxYears with descriptions and defaults. The description adds context like annual fiscal years only, which affects maxYears interpretation, but it doesn't add per-parameter syntax or constraints beyond the schema. 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 gets a company's revenue disaggregated by segment, geography, and product/service, plus operating income when tagged. This specific verb+resource+dimensions structure distinguishes it from sibling tools like GetFinancialStatement and GetFinancialFact, which are explicitly referenced for consolidated figures.

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 description provides concrete usage rules: annual fiscal years only, latest restated values, one table per axis, and warnings about overlapping rows. It explicitly directs users to GetFinancialStatement or GetFinancialFact for consolidated revenue, giving clear when-to-use and when-not-to-use guidance.

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