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

Annotations already declare readOnly/idempotent/non-destructive, so the safety profile is covered; the description adds genuinely new behavioral context: an access prerequisite (verified account identity or linked API key), a consent/privacy constraint on what aggregates are visible, and an explicit caveat that rates are correlational cohort data, not causal or predictive claims. This goes well beyond what the annotations convey.

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?

Three sentences, each carrying distinct information (what is returned, what access is required, what the numbers mean), with the core purpose front-loaded. Slightly heavy noun stacking in sentence one costs it a 5.

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?

An output schema exists so return structure needn't be explained, and the description covers the remaining agent-relevant unknowns: auth prerequisite, data-visibility scoping, and interpretation limits. Only the missing 'when to use versus sibling tools' guidance keeps it short of complete.

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 tool takes zero parameters, so there is nothing for the description to disambiguate; baseline 4 applies. No misleading parameter language is present.

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?

States a specific read operation on recorded opportunity outcomes and separates the two data sources it returns: private evidence/failure feedback and consented public aggregates. It is distinguishable from siblings like get_opportunity_workspace, though the phrasing ('evidence funnel', 'sufficiently diverse, jointly consented public outcome aggregates') is dense enough that an agent may need a second read to be sure.

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?

Usage is only implied — the description establishes this is a review/learning read but never says when to call it instead of get_opportunity_workspace or research_opportunity_workspace, nor any exclusion such as 'call after a lead search completes'. No explicit trigger or alternative is named.

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