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

Annotations already declare readOnlyHint=true, destructiveHint=false, and idempotentHint=true, covering the safety profile. The description adds valuable context beyond annotations: it explains the evidentiary basis of each kind (sworn on Form ADV Item 4, re-registration rule, SEC roster departure) and honestly discloses that roster_exit reasons are not stated. This is useful behavioral disclosure for a data-search tool.

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 and information-efficient, front-loading the core distinction (three factual sources) before the filter options and exclusions. Each sentence earns its place, though it runs slightly long; the density justifies the length.

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?

With no output schema present, the description carries the burden of explaining return values, and it does — listing target/acquirer dfx:ria ids, date, headline, magnitude, and source for each row. Combined with the filter list and the no-schema safety annotations, an agent has enough to call this tool correctly.

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 44% (below the 50% threshold), so the description should compensate. It partially does: it explains the meaning of the kind values (which the schema only lists as an enum) and notes that min_advisors applies only to absorbed events and that magnitude is expressed as advisor count or RAUM. However, it does not add detail for parameters like limit, cursor, or firm_dfx_id beyond what the sparse schema provides.

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 names a specific verb (search) and resource (RIA M&A events) and enumerates the three factual sources (succession, absorbed, roster_exit) with precise definitions for each. It explicitly carves out what the tool is not — 'No press, no rumours, no predictions' — which distinguishes it from sibling search tools like search_ria and search_ria_advisor_moves.

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 clearly states the filtering axes (kind, acquirer/target CRD, firm id, date window, minimum advisors) and defines the semantic of each kind. It conveys the intended use case — filed facts rather than news — via the 'No press, no rumours, no predictions' exclusion, giving clear context for when to prefer this tool even though it doesn't name sibling alternatives explicitly.

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