neuron_find_elements

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

With no annotations, the description carries the full burden of behavioral disclosure, and it only states the search mechanisms. It does not reveal what the tool returns (element references? count? text?), what happens when nothing matches, whether matching is exact or partial, or whether results are scoped to visible elements only. This is a significant gap for a tool with no output schema.

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 9-word sentence with zero fluff, and the core search mechanisms are front-loaded. However, it is so terse that it borders on under-specification; the conciseness is efficient but earned at the expense of the usage and behavioral context that other dimensions penalize.

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 tool with no annotations, no output schema, 4 parameters, and a large sibling set containing several overlapping DOM tools, a one-sentence description is inadequate. It fails to explain return format, how results can be consumed by interaction tools like neuron_click or neuron_type, or how it differs from neuron_query_dom. An agent cannot confidently invoke this tool correctly in context.

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 100%, so the baseline is 3. The description adds minimal value beyond the schema: 'CSS selectors' and 'visible text' loosely map to the selectors and texts parameters, but the schema already describes them nearly identically. The description does not clarify relationship between the parameters, matching semantics, or the limit behavior.

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?

'Find elements by CSS selectors or visible text' states a specific verb (find), resource (elements), and the two matching mechanisms (CSS selectors, visible text). It is clear and self-contained, but it does not explicitly differentiate itself from the closely related sibling neuron_query_dom, so an agent could not tell them apart without opening both schemas.

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 gives no guidance on when to use this tool versus alternatives such as neuron_query_dom, neuron_evaluate_js, or neuron_watch_element. No context, exclusions, or alternative routing is provided, leaving the agent to guess which of the many DOM-related siblings is appropriate.

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