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

Annotations already declare the tool read-only, idempotent, and non-destructive, yet the description adds substantial behavioral context beyond them: the free-tier row cap (first 5 rows plus locked.count/locked.by_type), the record-level truncation (first 3 names per section), and the hard exclusion of contact values and decision-maker names. It also discloses how the tool reports its own withholding via entitlement and locked, which is exactly the kind of trait an agent needs to interpret a partial result.

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 well front-loaded: the first sentence establishes purpose and scope before the access model. The trailing promo line ('Full access: DFX Intelligence, 7 days free at ...') is arguably not part of the tool's selection semantics and slightly dilutes an otherwise tight, information-dense description.

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, the description does the work of explaining the return shape (entitlement, locked, locked.count, locked.by_type) and the empty-result semantics, which is strong compensation. The main residual gap is the undocumented within_days semantics, so it is not fully complete for a two-parameter analytic tool.

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 50%: dfx_id is thoroughly documented with its full id-prefix taxonomy in the schema, but within_days carries only a default and no stated meaning. The description references 'the window' and recent evidence but never explains what within_days controls or its units beyond the schema default, so it does not fully compensate for the coverage gap.

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 and resource and enumerates the concrete evidence types it returns (recent filings, vehicles formed, people moves, fundraising, transition signals, loan maturities), which lets an agent distinguish it from generic readers like get_entity. It never explicitly names a sibling tool to differentiate against, so it stops short of a 5.

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 usage context is implied by the content list and by the note that an empty result means 'no observed change in the window,' which is a useful interpretation cue. But there is no explicit when-to-use statement and no guidance on choosing this over changes_since, search_signals, or who_should_care, leaving the routing decision to inference.

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