Compute the exact factorial of any integer up to 10,000 using arbitrary-precision arithmetic, avoiding overflow errors common with floating-point calculations.
Compute n! exactly using arbitrary-precision integer math (avoids float64 overflow past ~18)
| Name | Required | Description | Default |
|---|---|---|---|
| n | Yes |
Changes observed during successful MCP inspections.
v2.0.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the behavioral disclosure burden. It states that computation is exact and arbitrary-precision-less, and specifically warns about float64 overflow past ~18, which is useful behavioral context beyond the schema.
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 single sentence, immediately front-loaded with the operation 'Compute n! exactly', and adds only one clarifying detail about precision. It is easy to scan and parse.
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 simple, deterministic math function with one input and no side effects, the description plus the schema is nearly complete. It could mention output size or the n=0 edge case, but nothing critical is missing for selection or invocation.
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 supply meaning. It implies n is the factorial argument, but it does not mention edge cases such as 0! = 1 or the allowed range up to 10000, leaving the schema to carry those details.
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 uses a specific verb ('Compute') and identifies the exact operation (n!) plus the mathematical domain (arbitrary-precision integers). This clearly separates it from general calculation tools and from combinatorial siblings like permutations and combinations.
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 purpose is clear enough to infer when factorial is wanted, and the note about avoiding float64 overflow hints at when exactness matters. However, it does not explicitly name alternatives or state when not to use this tool versus siblings like 'calculate' or 'combinations'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.