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

With no annotations, the description carries the full behavioral burden. It usefully discloses that either metric can be computed ('and/or') and defines the formulas, which signals the optional-parameter model, but it omits authentication expectations (the api_key param), error behavior, and whether both metrics return together.

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?

A single front-loaded sentence with the metric names and formulas; no filler. Every clause earns its place by defining the two computable quantities.

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?

An output schema exists, so return values need not be explained, and the description covers which inputs feed which metric. It is nearly complete for a 4-param calculation tool, with the only real gap being api_key and units handling.

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 0%, so the description must compensate. It maps mass_waste_kg to E-factor and mass_all_inputs_kg to PMI over mass_product_kg, adding real meaning beyond the bare schema. It leaves api_key completely undocumented, keeping it from a 5.

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?

States a specific verb ('Calculate') and resource ('green chemistry metrics') and defines both outputs (E-factor, PMI) with their formulas. The tool is unique among its siblings, so no sibling differentiation is strictly needed, but it stops short of a 5 by not clarifying the relationship to metrics-adjacent siblings like covabasic_stoichiometry.

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 'and/or' phrasing implies either metric is obtainable, but there is no guidance on when to use this tool, what prerequisites exist, or which sibling to pick instead. Usage is only weakly implied.

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