neuron_query_dom

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It implies a read-only snapshot but does not state what the returned snapshot looks like, whether it waits for the page to settle, or any side-effect/performance caveats.

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?

A single front-loaded sentence with an active verb, a clear resource, and scope. There is no filler or redundant 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 relatively simple tool with fully documented parameters, the description is mostly sufficient to invoke it. However, since there is no output schema and no annotations, the description does not explain the shape of the returned DOM snapshot, which an agent would need to reliably consume the result.

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?

All three parameters are fully described in the schema with defaults, so the description adds little beyond the schema. 'Active page or targeted subtree' loosely maps to the body default and selector parameter, but provides no new semantic detail.

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 action ('Capture') and resource ('DOM snapshot'), and scopes it to the active page or a targeted subtree. It is clear, though it does not explicitly differentiate from closely related siblings like neuron_find_elements or neuron_evaluate_js.

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 implies the tool is for capturing DOM snapshots, and the selector/depth parameters clarify the scoping. However, it provides no explicit guidance about when to prefer a sibling tool or when not to use this one.

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