math_factorial_calculator

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

With no annotations, the description discloses key behaviors: uses BigInt, exact decimal results, n up to 10000. It does not mention mutability or side effects, but being a calculator, it is assumed read-only. The description is honest about its capabilities.

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 concise (3 sentences) and front-loaded with tool identity and core operations. It avoids unnecessary words and provides a reference to the full guidance tool.

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?

Given no output schema and many siblings, the description covers essential aspects: operations, constraints, and reference to describe_tool. It could be more complete by detailing parameter options, but is sufficient for a simple calculator 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?

The description lists the operations but does not specify the exact string values expected for the 'operation' parameter (e.g., 'factorial', 'permutations'). With 0% schema coverage, the description should provide more explicit parameter guidance.

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 clearly states the tool computes factorial (n!), double factorial (n!!), permutations (nPr), and combinations (nCr) with BigInt for n up to 10000. It distinguishes itself from sibling math tools by explicitly listing its specific operations.

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 description provides clear context on what the tool computes, but does not explicitly state when not to use it or name alternatives. It suggests using describe_tool for full guidance, which implies the tool is for basic factorial/permutation/combination calculations.

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