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

Annotations already establish it is a read-only, idempotent, non-destructive, closed-world computation. The description adds behavioral value by stating the solver is flexible over which variable is unknown and returns the fourth, which is not derivable from the annotations alone.

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 formula and the input/output contract are front-loaded, and every clause carries information. No filler sentences.

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 4-param pure calculator with an output schema and full annotation coverage, the description is essentially complete. The only omission is disambiguating from calculate_solution_dilution, which would have fully closed the loop.

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%, with each of c1/v1/c2/v2 labeled (initial/final concentration/volume). The description's formula adds the relationship between them but no format or unit guidance beyond the schema, so baseline 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?

States a specific action ('compute dilution'), the exact formula C1·V1=C2·V2, and the operation mode (solve for any unknown). An agent can immediately tell this apart from generic calculators in the large sibling list.

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?

Gives clear domains ('chemistry, lab work, pharmacy') and the input condition (any 3 of C1, V1, C2, V2). It does not, however, distinguish itself from the very similar sibling calculate_solution_dilution, which is the main source of selection ambiguity.

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