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

Annotations already indicate readOnly=false, idempotent=false, and destructive=false. The description adds valuable context by stating that the operation 'queues the extraction,' which reveals asynchronous behavior and that leads are added to the pool. No contradiction with annotations.

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 description is a single, front-loaded sentence: 'Run a lead source now to pull new leads into the pool (queues the extraction).' It contains no filler and communicates purpose and behavior efficiently.

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?

Given a simple one-parameter trigger with annotations and no output schema, the description sufficiently covers purpose, effect, and the queued/asynchronous nature of the operation. It could mention return behavior or error cases, but these are not critical for this low-complexity 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?

The input schema provides 100% coverage for the single parameter 'id' with the description 'Lead source UUID.' The tool description does not add additional parameter-specific meaning, so it rests at the baseline for fully-schema-covered parameters.

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 clearly states a specific action ('Run') on a specific resource ('lead source') and the intended effect ('pull new leads into the pool'). It also notes the queued extraction behavior. However, it does not explicitly differentiate from related sibling tools such as neuron_extract_leads or neuron_create_lead_source.

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 phrase 'Run a lead source now' clearly conveys immediate/manual execution, and the context of pulling new leads into the pool implies when this tool is appropriate. It does not provide explicit exclusions or alternatives, so it falls short of full guidance.

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