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

No annotations and no output schema, so the description carries the full behavioral burden. It does disclose a meaningful trait - Fowler's algorithm with a sum-preserving invariant - but says nothing about edge cases (zero/negative ratios, weighted vs sequential ratios), error behavior, or return shape.

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: verb, resource, algorithm, and guarantee with zero filler. Nothing to trim and the key invariant is stated up front.

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 self-contained arithmetic operation the algorithm and invariant go a long way, but with no annotations, no output schema, a nested object, and 0% schema coverage, the absence of parameter semantics and return-format detail leaves real gaps.

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% and the payload nests two fields, so the description must compensate. It implies a cents integer (amount_cents) and weighted ratios (ratios), but never explains what a ratio represents, whether weights are relative or sequential, or output ordering.

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 (split) and resource (an integer amount of cents among N ratios), and adds the guarantee that parts sum back to the original. This clearly distinguishes it from money_format and the numeric siblings, though it doesn't name an alternative explicitly.

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 'zero rounding loss' guarantee implies when to reach for this over simple division, but there is no explicit when-to-use statement, no prerequisites, and no named alternative among the money/number siblings. Usage is only inferable.

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