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

Annotations already declare readOnly, idempotent, non-destructive, closed-world, so the safety profile is covered. The description adds genuine behavioral context beyond that: paging filters assets rather than group labels, group_id must be an exact returned scope_id, and evidence should be read via research_read_evidence since counts alone don't identify members. It lacks return-format detail, but an output schema exists.

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 routing statement and exclusion are front-loaded, and the Selection/Presentation/Evidence labels keep the dense text navigable. It is longer than strictly necessary, but nearly every sentence carries actionable 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?

For a 4-param discovery tool with an output schema and full annotation coverage, the description supplies the routing, ID-resolution, paging, and evidence workflow an agent needs. Return-value explanation is rightly omitted given the output schema; only minor gaps remain.

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%, so the baseline is 3, but the description adds real nuance beyond the schema: 'Paging filters assets, not group labels', the requirement to reuse exact returned scope_ids, and the offset/query coupling ('use returned next_offset with the same query/group filter'). This meaningfully clarifies otherwise easy-to-misuse parameters.

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 states a specific verb+resource (resolving asset names/symbols and checking governed taxonomy membership) and names the exact sibling tools it is not (research_markets, research_compare_cohorts). An agent can distinguish this from the many research_show_* and cohort tools without opening any schema.

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?

It gives explicit when-to-use ('resolving an asset name/symbol or checking governed taxonomy membership'), when-not-to-use with named alternatives, and a concrete example ('Which assets belong to DeFi?'). Routing is unambiguous.

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