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

Annotations already declare read-only, non-destructive, non-open-world behavior, and the description adds real context: climate data and carbon factors come from the caller and 'nothing is guessed,' plus that shading factors are measured on the scene's own sun paths. It does not address failure modes or validation limits, so it falls short of a 5, but it adds meaningful behavioral context beyond the annotations.

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?

Front-loaded with a WHEN clause and organized into method → inputs → exclusions, so the key routing signal arrives first. It is dense and heavy with parentheticals, making it a wall of text, but for a 16-parameter tool with no output schema nearly every clause carries information.

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?

There is no output schema, so the description must convey return content — and it does, listing the computed outputs (heating need, DHW, final/primary consumption, embodied carbon, summer check). Combined with its statement of external data dependencies, an agent has enough to call and interpret 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%, so the baseline is 3. The description goes further by clarifying the role of caller-supplied inputs — climat (degree-days, irradiation), facteurs_carbone (emission factors), and systeme (generator) — and explains that quantities are derived from the bill of quantities, linking semantics to specific parameter groups. This is useful context beyond the schema text.

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 verb+resource (estimating energy performance) and enumerates exactly what is computed: heating need via degree-day method, DHW, final/primary energy, embodied carbon, and a summer overheating check. It explicitly differentiates from the sibling cao_re2020 by stating it is 'NOT a French DPE nor the regulatory RE 2020 calculation,' so an agent can route correctly.

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 WHEN clause specifies the triggering user intents (cost to run, climate cost, summer overheating) and the closing sentence gives an explicit exclusion and implicit alternative (cao_re2020). Both when-to-use and when-not-to-use are stated, which is the top of the scale.

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