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

Annotations already mark the tool as read-only, open-world, idempotent, and non-destructive. The description adds valuable behavioral context beyond annotations, including experimental status, the meaning and limitations of lift and base_rate, forward-cohort resolution dates, a 1-unit cost, and an end-user restriction.

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 compact and front-loaded with the core purpose, followed by necessary caveats and cost information. Every sentence adds relevant operational or interpretive value, with no redundant or filler content.

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?

The description covers output-related cautionary context and cost but omits essential input parameter semantics and does not describe the output structure beyond lift and base_rate. Given the lack of an output schema and parameter descriptions, it is not sufficiently complete for confident invocation.

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 input schema has two parameters—domain and org_id—with no descriptions, and the description makes no mention of either parameter. With 0% schema description coverage, the tool description fails to explain what these inputs mean or how they affect the forecast.

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's purpose: producing an experimental forecast of specific company actions (raise, be acquired, acquire, hire an executive) from FundzScore v3. It is concrete and distinct from sibling tools that focus on events, watchlist diffs, or causal explanations.

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 important usage cautions: treat lift as a ranking aid, base_rate is a population mean, cohorts resolve on specific dates, and do not present predictions to end users. However, it does not explicitly say when to choose this tool over the sibling tools or provide selection criteria.

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