set_regulation_mode

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions that the tool 'Controls the overall heating system behavior' and describes the modes, but it does not disclose critical behavioral traits such as whether this requires specific permissions, if changes are reversible, potential side effects (e.g., system downtime during bleeding modes), or rate limits. For a mutation tool with zero annotation coverage, this is a significant gap.

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 appropriately sized and front-loaded. The first sentence states the core purpose, and the second sentence elaborates on the modes with clear examples. Every sentence adds value without redundancy, making it efficient and easy to understand.

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?

Given the tool's complexity (a mutation tool with one parameter but significant behavioral implications), no annotations, and no output schema, the description is partially complete. It covers the purpose and parameter semantics well, but lacks details on behavioral aspects like permissions, reversibility, or system impact. For a tool that controls heating system behavior, more context on safety or operational constraints would be beneficial.

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?

The description adds meaningful context beyond the input schema. The schema has 100% coverage with an enum for 'mode' and a description that mirrors the tool description. However, the tool description provides additional semantics by explaining the purpose of each mode: 'heating' for normal operation, 'off' to disable heating, and bleeding modes for maintenance. This clarifies the practical use of the parameters, compensating for the lack of detailed schema annotations.

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 the tool's purpose: 'Set the heating regulation mode. Controls the overall heating system behavior.' It specifies the verb ('Set') and resource ('heating regulation mode'), but does not explicitly differentiate it from sibling tools like 'set_dhw_mode' or 'set_preset', which likely control different aspects of the heating system. This makes it clear but not fully distinguished from alternatives.

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?

The description provides implied usage guidelines by listing the modes and their purposes: 'heating' for normal operation, 'off' to disable heating, or bleeding modes for system maintenance. However, it does not explicitly state when to use this tool versus alternatives like 'set_dhw_mode' or 'set_preset', nor does it mention any prerequisites or exclusions. The guidance is useful but not comprehensive.

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