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

Annotations only declare readOnlyHint=true, so the description carries the full behavioral burden. It exceeds expectations by disclosing the depth_confounded caveat, pricing structure (per result, per record, cap, included plans), and the purpose of the context parameter. It also clarifies that context is never used for ranking. This is rich, non-obvious behavioral context.

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 front-loaded with the core purpose, then adds returns, a unique value proposition, a critical caveat, and pricing. While it is somewhat verbose, every sentence adds value—pricing and estimate guidance are useful for an agent. It is not overly redundant, though the pricing details could arguably be moved to an external reference. Still, it is well-structured.

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?

Despite the lack of an output schema, the description tells an agent exactly what to expect: distributions, deltas, and the depth_note field. It also explains the depth_confounded caveat, pricing, and context usage. For a 3-parameter tool with no output schema, this is complete: an agent knows what it does, what it returns, and how to interpret results.

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% and the schema already describes both a and b parameters with examples. The description does not add any additional parameter semantics; it only mentions parameter behavior indirectly (e.g., context purpose), which is already in the schema. Baseline 3 is appropriate since schema does the heavy lifting.

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 'two markets side by side on one rubric' and lists exactly what it returns (distributions, deltas on score, agent readiness, facets, adoption rates). It distinguishes itself from sibling tools like cohort_scores (single cohort) and compare_providers (providers rather than cohorts) with a specific verb and resource.

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 clear context: it is the tool for comparing two cohorts, and even illustrates with a concrete question ('is US payments further along than UK banking?'). It implies when to use it (when a cross-market comparison is needed) but does not explicitly name alternatives or exclusions, so it falls short of a 5.

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