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

Beyond the standard annotations (readOnlyHint: true), the description provides rich behavioral context about the data itself, including the specific snapshot date (6 Oct 2026 close), the methodology (scoring against S&P 500 and various yield buckets), and the inclusion of specific call types (Edgarette’s 12-month expected-return calls).

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 dense but highly efficient; every clause serves a function, whether defining the data set, the methodology, or the usage disclaimer. There is no superfluous language.

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?

Given that the tool has no input parameters and no defined output schema, the description bears the entire burden of definition. It successfully communicates the precise scope, historical boundary, and complex nature of the data set.

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?

Since there are zero input parameters, the description cannot elaborate on parameter meaning. Following the rule for 0 parameters, a baseline score of 4 is appropriate, as the description is otherwise highly effective.

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 tool's purpose is specific: it provides a historical, quantitative performance audit of the board's investment calls. It clearly defines the resource (the board's calls) and its unique characteristics (locked, SHA-256 receipt, scored).

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 includes a vital behavioral boundary: 'A test of the boards, not advice.' This immediately guides the agent on the appropriate context for using this historical performance data, preventing it from being misapplied as predictive advice.

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