joules_per_verified_task

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

With no annotations, the description carries the full behavioral burden. It clearly discloses the calculation formula, optional parameters with defaults mirroring an interactive calculator, and the response contents including result, formula, interpretation, and a cite_as sentence. It does not mention edge cases like zero pass rate, but the core behavior is transparent.

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 compact and every sentence earns its place: purpose, formula and insight, defaults/source, and response contents. There is no filler, and the important formula is front-loaded immediately after the purpose statement.

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 stateless calculator with six optional parameters and no output schema, the description sufficiently explains what the tool computes, what the inputs default to, and what the response will contain. The only minor gap is the lack of explicit guidance on how model A and model B should be ordered, but the schema names make that reasonably clear.

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 description coverage is 100%, so the baseline is 3; the description adds value by explaining how the parameters combine in the formula and what the result means. It also clarifies that all six parameters have defaults, giving operational meaning beyond the individual property descriptions.

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 names a specific metric (joules per verified task), gives the formula E = tokens × J/token ÷ pass rate, and frames the tool as a model comparison for energy efficiency. It is clearly distinct from energy-only sibling tools because it divides by pass rate, though it lacks a direct imperative verb like 'calculate' or 'compare'.

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 implies use for comparing energy efficiency per verified task and states that all parameters are optional with defaults, which tells the agent it can call with zero arguments. However, it does not explicitly name when to choose this tool versus alternatives such as llm_energy or verification_bottleneck, so usage routing is inferred rather than explicit.

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