math.integrate_simpson

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

Annotations already declare readOnlyHint, openWorldHint=false, and idempotentHint=true. The description adds valuable behavioral context beyond those: float64 computation, 12 significant digits, an error when a > b (requiring manual sign flip), and inaccuracy near singularities.

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 a compact paragraph that front-loads the operation, then gives parameter constraints, then caveats. Every sentence adds information, though a slightly more structured layout would improve scanability.

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 annotations covering safety/idempotency and an output schema present, the description is largely complete: it covers method, syntax, bounds, sample count, precision, and singularity limitations. The missing explanation of the variable parameter and absence of explicit sibling-selection guidance are the main 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%, so the description must carry parameter meaning. It explains expression syntax (core.calc), that a and b must be Decimal strings with a < b, and that n is an even integer from 2 to 20000 with default 100. It omits the variable parameter entirely.

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 (구한다) and resource (정적분 ∫_a^b f(x) dx), and names the exact numerical method (합성 심프슨 1/3 법). This method name implicitly distinguishes it from sibling math.integrate_gauss_legendre and other integration tools.

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?

Usage is implied by the purpose (approximate definite integrals), and it warns that intervals with singularities are inaccurate. However, it never explicitly states when to choose this over gauss_legendre or symbolic methods, nor does it name alternatives.

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