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

Annotations already declare readOnly, idempotent, non-destructive, and closed-world, so the safety profile is fully covered. The description adds the useful behavioral trait that the result is returned in lowest terms, but says nothing about edge cases such as a zero denominator or division-by-zero errors.

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?

Three short sentences, front-loaded with the operation and result before the usage note and cross-reference. No filler, though the list_bundles sentence is tangential to calling this tool correctly.

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?

With an output schema covering return values and annotations covering the safety profile, the description only needs to convey the operation set and simplified-result behavior, which it does. Nothing essential for correct invocation is missing.

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 all five parameters are already documented, and the description merely restates them as "num1/den1, op, num2/den2". It also abbreviates the parameter as "op" while the schema names it "operation", a minor inconsistency that adds no meaning.

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 precise verb set (add/subtract/multiply/divide) and resource (two fractions) plus the output transformation (simplified result). This distinguishes it from near-neighbors like calculate_fraction, calculate_ratio_simplify, and calculate_gcd_lcm, which an agent could otherwise confuse it with.

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?

"Use for math homework" gives an implied context but no explicit when-to-use vs. when-not, and no comparison against the many other math/arithmetic siblings (calculate_fraction, calculate_equation, calculate_ratio_simplify). The pointer to list_bundles is a cross-reference, not selection guidance.

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