percent_change

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

No annotations are provided, so description carries full burden. It discloses that it computes percent change and absolute delta, but doesn't specify return format (e.g., object vs. number), edge cases like division by zero when 'from' is 0, or rounding behavior.

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?

One efficient sentence that front-loads the core function and the additional delta output. No filler or redundant text.

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?

No output schema exists, and the description only hints at output via 'absolute delta.' It does not explain the return structure, number formatting, or how invalid inputs (e.g., from=0) are handled, leaving some uncertainty for an agent invoking the tool.

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% ('Starting value' and 'Ending value'), so description adds no new parameter semantics beyond mapping 'from/to' to 'old → new.' This is baseline for full schema coverage.

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?

Clear and specific: 'Percent change from old → new value (and absolute delta)' states the exact computation. Distinguishes from siblings like diff_text (text diff) and unit_convert (unit conversion).

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?

No guidance on when to use this tool versus alternatives. Does not mention any exclusions or note that it's for numeric comparisons only.

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