neuron_workflow_status

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

With no annotations, the description carries the full burden, and it handles this well for a simple getter: 'Get' signals a read-only operation, and the parenthetical enumerates the possible status values an agent should expect. It does not detail the exact return shape, but the behavior is sufficiently disclosed for a zero-parameter status query.

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 includes both the action and the full set of meaningful state values, making it maximally concise and informative.

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 low-complexity, parameterless getter with no output schema, the description provides the core information an agent needs: what the tool does and what the possible outputs are. The only minor gap is not specifying the exact response format, but the enumerated statuses largely compensate for the missing output schema.

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 no parameter meaning for the description to add. The baseline of 4 for parameterless tools applies.

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 the specific verb 'Get' with a clear resource, 'current workflow engine status', and enumerates the possible values (idle, recording, replaying, demo). This distinguishes it from control tools like neuron_start_recording or neuron_stop_replay and from list-style tools like neuron_list_workflows.

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 intended use is implied: call this when you need to know the current workflow engine state. However, it does not explicitly state when to prefer this over related tools or mention any exclusions, so guidance remains implicit rather than explicit.

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