Required heating power
required_heating_powerEstimate required heating power with an optional reserve.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| heat_loss_kw | Yes | ||
| reserve_percent | No |
required_heating_powerEstimate required heating power with an optional reserve.
| Name | Required | Description | Default |
|---|---|---|---|
| heat_loss_kw | Yes | ||
| reserve_percent | No |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, so the safety profile is covered. The description adds minimal behavioral context by mentioning an optional reserve, implying the reserve parameter affects the estimate. However, it does not describe output format, assumptions, or any limitations, so it only marginally exceeds the annotation baseline.
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, efficient sentence with no fluff. It is front-loaded with the verb and resource. While terse, it is appropriately sized for the tool's simplicity, similar to the update_drive example that scored 4.
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 no output schema and a single-line description, the tool is underspecified. The agent is not told what the output represents (e.g., required power in kW), how the reserve is applied, or any assumptions about the calculation. For a 2-parameter tool, this is minimally viable but leaves key context missing.
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%, and the description does not explain the parameters at all. It mentions 'reserve' generically but does not map it to reserve_percent or explain that heat_loss_kw is the primary input. The description adds no value beyond the bare parameter names in the schema, failing to compensate for the lack of schema documentation.
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 (estimate) on a specific resource (required heating power) with a modifier (optional reserve). It is distinct from sibling tools that focus on heat loss or boiler capacity, though it does not explicitly name a sibling to differentiate from. The purpose is clear enough for an agent to understand what it does.
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 guidance on when to use this tool versus alternatives such as boiler_capacity_check or heat_loss_total. The description does not mention prerequisites, exclusions, or typical scenarios, leaving the agent to infer usage from the name and parameters.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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