list_nulls

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

With no annotations, the description carries the full behavioral burden, and it does disclose meaningful context beyond the name: each entry ships with a 'positive control' and the museum includes DeepMap's own retractions. That tells the agent something real about data trustworthiness. However, it says nothing about pagination, ordering, the effect of 'limit,' response size, or permissions, so the disclosure is partial.

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 purpose is front-loaded and the whole description is short, but the trailing sentence 'We carry our own retractions; that is the credibility' is rhetorical positioning that consumes space where parameter or return-shape detail was needed. Two of three sentences earn their place.

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?

The tool has no annotations, no output schema, and zero parameter documentation, so the description should do more work. It partially compensates by describing what each returned item contains (the positive control), but omits limit/pagination semantics, domain value expectations, and return structure, leaving an agent under-informed for invocation.

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 description coverage is 0% for both parameters, so the description must compensate. It explains 'domain' as an optional filter but gives no format, valid values, or enumeration for it, and says nothing at all about 'limit' (default, maximum, or truncation behavior). Half the parameters remain completely opaque.

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 gives a specific verb ('List') and a concrete resource ('DeepMap's documented nulls / bounds / retractions (the Null Museum)'), so an agent can tell this is a catalog of documented negative/limiting findings. It does not explicitly distinguish itself from the many sibling tools (verify, ground_truth, capabilities), but the resource is specific enough to be identifiable.

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 only usage hint is 'optionally by domain,' which describes a parameter, not a when-to-use condition. There is no guidance on when this tool is preferable to verify, ground_truth, or check_hypothesis, nor any stated prerequisites or exclusions. An agent must infer the use case from the resource name alone.

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