llm_energy

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

With no annotations, the description carries the full transparency burden. It discloses that the response includes 'result, formula, interpretation and a ready-to-quote cite_as sentence,' and clarifies default behavior. It does not reveal the actual formula or assumptions, but for a simple calculator tool this is solid behavioral disclosure.

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 three concise sentences: purpose, parameter/default behavior, and output shape. It is front-loaded and contains no filler or redundant restatement. Every sentence earns its place.

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?

For a simple calculator with fully documented parameters, the description covers purpose, optional invocation, default source, and response structure. The main omissions are explicit sibling differentiation and more detail about the 'real-world equivalents,' but the definition is complete enough for an agent to invoke the tool correctly.

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 coverage is 100%, and every parameter already has a description and default value. The description adds only the general note that all parameters are optional and defaults mirror the calculator, which is modest extra value. With the schema doing the heavy lifting, the baseline score of 3 is appropriate.

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 identifies the tool as an electricity/cost/CO₂ calculator for AI queries, with the specific conversion 'Tokens → Wh, joules, dollars, CO₂ and real-world equivalents.' The purpose is immediately understandable and distinct from pure cost tools in spirit. However, it does not explicitly distinguish itself from sibling tools like token_cost, so it falls just short of a 5.

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 says all parameters are optional and defaults mirror the interactive calculator, which is useful invocation guidance. But it provides no explicit when-to-use guidance or alternatives, and none of the sibling tools are mentioned. An agent must infer when llm_energy is the right choice versus token_cost or model_routing.

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