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

No annotations are provided, so the description carries the burden. It discloses the calculation method, the source, and the return values (oven-dry mass, water mass, tonnes). However, it does not disclose edge cases like what happens if both species and basic_density_kg_m3 are provided, or if mc_pct is omitted (defaults to species' freshly-felled MC). The description adds some behavioral context but not comprehensive detail.

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 two sentences, front-loaded with the formula and scope, and includes the source and return values. It is efficient and structured, though the list of species could be seen as slightly verbose. Overall, it 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 calculation tool with 4 parameters, 100% schema coverage, and no output schema, the description is fairly complete. It explains the formula, the source, the presets, and the return values. It could be more complete by explaining the precedence between species and basic_density_kg_m3, and the default MC behavior, but these are minor gaps given the schema already documents defaults.

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 schema already documents all four parameters. The description adds context about the formula and the species presets, but does not add much beyond the schema. Baseline 3 is correct because the schema does the heavy lifting.

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 states a specific verb ('Weight of a roundwood/log batch'), the resource (roundwood/log batch), and the formula (W = volume x basic density x (1 + MC/100)). It also names the source (USDA Wood Handbook 2021 Ch.4) and distinguishes itself from siblings like lumber_weight_calculator and log_volume by focusing on roundwood/log batch weight at any moisture content. This is a clear, specific purpose that an agent can act on.

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 when to use this tool: when you need the weight of a roundwood/log batch at a given moisture content, with presets for species or custom density. It does not explicitly state when not to use it or name alternatives (e.g., lumber_weight_calculator for sawn lumber), but the formula and 'roundwood/log batch' scope provide clear context. A 4 is appropriate because the usage context is clear, though exclusions are not explicit.

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