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power_report

Assess power availability by comparing generation capacity to nameplate and measured machine draw, showing how much capacity is free at the moment.

Instructions

Generation capacity vs machine draw, nameplate AND measured.

Nameplate is what everything built would draw running at once. Measured weights each machine by the 300 s productivity monitor the save already carries, which on a factory with idle blocks is a very different number -- and it is the one that says what is free right now. Both are shown because they answer different questions.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
saveNo
worldNo
Behavior3/5

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

With no annotations, the description carries full burden. It explains the conceptual behavior (how measured is computed), but doesn't explicitly state whether the tool is read-only, possible side effects, or error conditions. It adds value but leaves some transparency gaps.

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

Conciseness5/5

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

The description is concise and well-structured. The first sentence gives a clear summary, and the second paragraph adds needed explanatory detail without unnecessary fluff. Every sentence earns its place.

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

Completeness3/5

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

The description explains the core conceptual distinction, but falls short on return format (no output schema) and parameter usage. Given the tool's simplicity, it's adequately complete for a knowledgeable user, but an agent would need more details to invoke it confidently.

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

Parameters2/5

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

Schema coverage is 0%, and the description does not mention the 'save' and 'world' parameters at all. The agent must infer their meaning from the tool name and optionality, which is insufficient given the schema provides no additional guidance.

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

Purpose5/5

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

The description clearly states the tool reports generation capacity vs machine draw, with both nameplate and measured values. It explains the distinction in detail, making the tool's unique purpose evident even among many siblings.

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

Usage Guidelines4/5

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

The description explains that measured values weigh by the 300s productivity monitor and are 'the one that says what is free right now,' giving clear context for when to use this tool. However, it doesn't explicitly mention alternatives or when not to use it.

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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