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

Annotations already cover safety (readOnlyHint=true, openWorldHint=false, destructiveHint=false), so the bar is lower, yet the description adds real behavioral context: the projection cap rule ('projections never exceed the measured coverage'), the foreign-issuer fallback, and the reliability caveat 'Estimates, not advice.' Missing details like pagination or data freshness keep this from a 5.

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 return contents are front-loaded in the first clause, followed by the fallback modes and the usage trigger. It is dense but every sentence carries information; the multi-clause first sentence is slightly heavy but not padded.

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 and two optional parameters, the description responsibly covers both calling modes, the ranking cap behavior, the fallback for unranked issuers, and the estimate caveat. An agent has enough to call it correctly, though the shape of the numeric fields (yield units, currency) is left unspecified.

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 coverage is 100%, so the baseline is 3. The description goes beyond the schema by explaining what omitting 'symbol' actually yields (the highest-yielding payers and possible initiators) and by framing 'limit' as ranking rows, reinforcing the schema text rather than merely repeating parameter names.

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?

Names a specific verb and resource ('Returns a company's dividend data') and then enumerates the exact contents: yield, per-share amounts, growth, cash-flow coverage, and observed payments. This is clearly distinguishable from sibling tools like get_financials or get_price_history, and the no-symbol fallback (highest-yielding payers, possible initiators) is stated up front.

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?

Explicitly states the triggering user intents: 'Use it when the user asks whether a company pays a dividend, how much, or which companies yield the most.' It also implicitly defines the two calling modes (symbol vs. omitted symbol). It stops short of naming an alternative tool or an explicit when-not-to-use case, so it is clear guidance without exclusions.

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