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

Annotations already carry readOnly/idempotent/non-destructive, so the description's job is to add data-quality context, which it does well: EPS is not normalized, past estimate revisions are unavailable, missing source rows/provenance are reported rather than filled, and consensus is capped at three future fiscal years. These are exactly the caveats an agent needs to avoid overclaiming, though it stops short of describing scale or latency behavior.

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 trigger sentence is front-loaded and clean, but the middle sentence is an overstuffed run-on chaining four separate data-scope clauses that would read far better as a list. Little is wasted informationally, but the structure makes the payload hard to parse on first read.

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 an output schema present, the description need not explain return shapes, and it still covers scope, the optional history parameter's effects, and the main data-integrity caveats. The remaining gap is the undocumented ticker format constraint, which is only enforced by a schema pattern.

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 only 50% (ticker is undocumented in-schema), but the description compensates by explaining what history_limit actually unlocks: up to 30 periods of selected metrics, quarterly P/E samples derived from monthly observations, and bounded source-native statement rows. The ticker parameter's accepted format lives only in the schema pattern, so the description does not fully carry the undocumented half.

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 concrete resource (ValuEdge financial history: profitability, growth, balance sheet, business quality, coverage) so an agent knows this retrieves fundamental data rather than prices or valuations. It does not explicitly contrast itself with the sibling get_stock_valuation, which is the nearest ambiguity, so it falls short of 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?

The opening clause 'Use this when the user asks for...' gives a clear trigger condition tied to user intent categories. It offers no explicit when-not or named alternative (e.g., use get_stock_valuation for price multiples), though the closing 'Do not infer a trade instruction' usefully bounds downstream use.

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