get_darwin_status

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

Beyond the annotations (readOnly, idempotent, etc.), the description adds meaningful behavioral context: it goes through the dAPI conversation rather than a raw TCP probe, which implies a higher-level interaction and potentially different latency or dependencies. It also explains the datafeed_enabled field's significance for historical tools.

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?

Two sentences, front-loaded with the core purpose, then valuable differentiation and a practical tip. No wasted words.

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?

The tool is simple (0 params, read-only) with an output schema available. The description covers purpose, usage, and adds behavioral context, making it complete for an agent to decide when to invoke it.

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 schema coverage is trivially 100%. The description doesn't need to elaborate on parameters, and the baseline for zero-parameter tools is 4.

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 the tool gets Darwin's connection status, release, and datafeed enablement. It explicitly differentiates from the sibling tool check_connection by noting it uses the dAPI conversation rather than a raw TCP probe.

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 provides explicit guidance on when to use this tool: when you need richer status than check_connection, and when you want to know if historical tools can work (via datafeed_enabled). It names the alternative and highlights the difference.

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