neuron_get_mocks

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

With no annotations provided, the description carries the full behavioral burden. 'List all active network mock rules' conveys a read-only operation and explicitly scopes results to active rules, which is useful. It could be more explicit about having no side effects, but the verb 'list' makes the non-mutating behavior reasonably clear.

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 with no wasted words. It states the action, the object, and the scope ('all active') 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?

For a zero-parameter, read-only list tool with no output schema, this description is nearly complete. It identifies what the tool returns (active network mock rules) and does not omit any required inputs. It could mention the return format, but the simplicity of the tool makes that a minor gap.

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 tool has zero parameters, so there is nothing for the description to explain about inputs. The baseline of 4 applies here, and the description correctly focuses entirely on the operation and result scope.

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 uses a specific verb ('List') and resource ('active network mock rules'), clearly distinguishing it from mutation siblings like neuron_set_mock and neuron_clear_mocks. The 'active' qualifier adds scope precision, so an agent immediately knows what this tool returns.

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 explicit guidance on when to use this tool versus alternatives. It does not mention that this is the read counterpart to set_mock or clear_mocks, nor does it state any situation where this tool should be preferred. Usage is only weakly implied by the verb 'List'.

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