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Tommertom

Plugwise MCP Server

by Tommertom

set_dhw_mode

Control domestic hot water heating modes: set to auto for scheduled heating, boost for immediate hot water, comfort for higher temperature, or off to disable DHW heating.

Instructions

Set the domestic hot water (DHW) heating mode for systems with hot water control. Auto mode follows the schedule, boost mode provides immediate hot water heating, comfort mode maintains higher temperature, and off mode disables DHW heating.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modeYesDHW mode: "auto" follows schedule, "boost" for immediate heating, "comfort" for higher temperature, "off" to disable
Behavior2/5

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

No annotations are provided, so the description carries full burden. It describes what each mode does (e.g., 'boost mode provides immediate hot water heating'), which adds behavioral context, but doesn't disclose critical traits like required permissions, whether changes are reversible, system state effects, or error conditions. For a mutation tool with zero annotation coverage, this is a significant gap in behavioral transparency.

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 appropriately sized and front-loaded, starting with the core purpose and then efficiently explaining each mode option in a single, well-structured sentence. Every sentence earns its place by adding specific value without redundancy or waste.

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?

Given the tool's moderate complexity (single parameter mutation), no annotations, and no output schema, the description is partially complete. It explains the purpose and parameter semantics well, but lacks details on behavioral aspects like permissions, reversibility, or system impacts. It's adequate for basic use but has clear gaps for safe agent operation.

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

Parameters4/5

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

Schema description coverage is 100%, so the schema already documents the single parameter 'mode' with enum values and descriptions. The description adds value by providing expanded semantics for each mode option (e.g., 'comfort mode maintains higher temperature'), which enhances understanding beyond the schema's basic enum descriptions. With only one parameter, the baseline is high, and the description compensates well.

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 verb 'set' and the resource 'domestic hot water (DHW) heating mode' with specific scope 'for systems with hot water control'. It distinguishes from siblings like set_temperature or set_preset by focusing exclusively on DHW mode control.

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 provides clear context by explaining when to use each mode option (e.g., 'Auto mode follows the schedule', 'boost mode provides immediate hot water heating'), but doesn't explicitly state when to use this tool versus alternatives like set_temperature or set_preset for similar heating controls. It implies usage through mode explanations but lacks explicit exclusions or comparisons.

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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