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Power draw of a set of components, and what runs it

calculate_power
Read-onlyIdempotent

Power draw of a set of components, and what runs it. The electricity calculator page's math. total_draw is the summed power; supply says how many of each power source covers it at its best output (needed); batteries gives each battery's runtime_minutes on a full charge, or enough_output: false when the load is above what that battery can deliver.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "components": "<components>"
    },
    "name": "calculate_power"
  }
}

Input Schema

NameRequiredDescriptionDefault
componentsYesComma-separated `shortname:quantity` pairs (display names work too; quantity defaults to 1). Components by shortname or name from /calculators/electricity.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

B3.2/5.0
Behavior3/5

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

Annotations already declare readOnly, idempotent, non-destructive and closed-world, so the safety profile is covered. The description does add real behavioral value by explaining the response shape (total_draw, supply/needed, batteries/runtime_minutes, enough_output: false), which matters since there is no output schema. It stops short of stating units, how unknown or invalid components are handled, or whether the calculation is purely additive.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Purpose is front-loaded in the first sentence and the remaining sentence is spent on the most valuable gap, the return structure. Slightly dense with backticked field names but no redundant wording.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a one-parameter calculation tool with no output schema, the description covers the essentials by documenting the result fields. Minor gaps remain: no units for total_draw, and no note on how unresolvable component names are reported.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100% and the single parameter carries its own format documentation (comma-separated shortname:quantity, defaults, examples). The description adds nothing about the components argument, so the baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a concrete subject (power draw of a component set) and adds the distinctive framing 'what runs it', plus names the exact calculator page it mirrors. It is clearly distinguishable from data-retrieval siblings like get_electricity_data, though it never names an alternative explicitly.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no when-to-use guidance, no prerequisites, and no mention of the obvious alternative (get_electricity_data for raw electricity data, get_best_defences for defence planning). The 'electricity calculator page's math' phrasing only hints at the use case; nothing tells the agent when to pick this versus a sibling.

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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