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

Beyond the annotations (readOnly/idempotent/openWorld/non-destructive), it discloses substantial behavioral context: the entitlement gating (first 5 rows full, rest as locked.count/locked.by_type with no rows), that contact values and decision-maker names are never returned, that every answer reports withheld data in `entitlement` and `locked`, plus data caveats (RAUM double counts affiliates, IAPD survivor bias before 2026-09-15, nothing predictive).

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 content is dense but front-loads the return shape and identifier format before the usage caveats, and the access boundary is stated crisply. It is a single unbroken block, and the trailing promotional sentence ('Full access: DFX Intelligence, 7 days free...') is not strictly definitional, which keeps it below 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?

For a 16-parameter, no-output-schema tool, the description is remarkably complete: it covers what is returned (compact cards with dfx:ria: ids), the fact-class provenance (reported/fact_from_registration/derived), entitlement/locked semantics, and the key data limitations an agent needs before trusting 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?

With 50% schema coverage, the description compensates well: it defines the accepted `query` formats (name, firm CRD, 801- SEC number, individual CRD with entity_type=advisor, 805- fund id) and groups the filters by entity type (firms by state/class/wealth_only/RAUM band/headcount/funds; advisors by firm CRD/state; funds by firm CRD/type). It does not address city, limit/sort/cursor, or every enum, so it stops short of full coverage.

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 and resource (search RIA firms, advisors and private funds) and enumerates the concrete data classes returned (Form ADV RAUM, clients by type, IAPD registration history, private funds). It explicitly distinguishes itself from siblings by naming search_pe_firms and search_vc_firms as the tools for private equity/venture managers as investors.

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-not guidance ('Not for private equity or venture managers as investors (search_pe_firms, search_vc_firms)'), explains the overlap case ('the same adviser may appear on both graphs (get_entity same_as)'), and documents the accepted query input formats for routing among entity_type values.

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