evaluate_datacenter_microgrid_ramp

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

No annotations are provided, so the description carries the full behavioral burden. It says what is computed but nothing about how the evaluation behaves: no indication of determinism, computational cost, sensitivity to the two inputs, or what happens when defaults are used. An output schema exists, but its mere existence does not explain the behavior of the calculation.

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 front-loaded sentence with no filler or repetition. It is appropriately sized, though it could carry one more clause of usage or parameter context without becoming bloated.

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?

With an output schema present, return-value explanation is not needed, and defaults reduce input burden. However, for a parameterized physics evaluation with 0% schema coverage and no annotations, the description leaves both input semantics and behavioral expectations unaddressed, so it is only minimally sufficient.

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 0% for the two numeric parameters, so the description must compensate and does not. It never mentions baseline_power_mwe or target_load_step_mwe, their units, or that the difference between them is the load step being assessed; only the parameter titles hint at this.

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 names a specific verb (evaluates) and three concrete outputs (microgrid stability, sCO2 turbine ramp times, thermal buffer sizing) scoped to AI data center training load spikes. That is clear and distinct from generic siblings like evaluate_coolant_bundle. It stops short of explicitly contrasting with the closely related evaluate_defense_microgrid_autonomy, so no sibling differentiation.

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?

There is no statement of when to use this tool versus alternatives, no prerequisites, and no exclusions. The domain phrase 'AI data center training load spikes' implies a context but it is inference, not guidance.

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