compute_e_limit

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

No annotations are provided, so the description carries full burden. While it explains what mathematical operation is performed, it lacks crucial behavioral details: it doesn't specify precision/accuracy characteristics, computational complexity, error handling for large/small n values, or what happens when n approaches infinity (practical implementation details). For a numerical computation tool with zero annotation coverage, this is insufficient.

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 efficiently structured in a single sentence that states the purpose and mathematical formula, followed by domain/category metadata. There's no wasted verbiage, and the core information is front-loaded. The parentheses for domain/category could be better integrated, but overall it's appropriately concise.

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 a numerical computation tool with 1 parameter, 0% schema coverage, no annotations, and no output schema, the description is incomplete. It explains the mathematical basis but misses implementation details, parameter guidance, accuracy information, and comparison to sibling tools. For proper agent usage, more context about practical computation considerations is needed.

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 compensate. The description mentions 'n' in the mathematical formula but provides no semantic explanation of what n represents (approximation parameter), appropriate ranges, or how choice of n affects accuracy. With one undocumented parameter and no additional guidance in the description, this leaves significant ambiguity for proper tool invocation.

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 the mathematical constant e using the limit definition, specifying the exact formula e = lim(n→∞) (1 + 1/n)^n. It distinguishes this from sibling tools like 'compute_e_series' by indicating a different computational approach (limit vs series). However, it doesn't explicitly differentiate from other mathematical constant tools beyond the formula mention.

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 minimal guidance on when to use this tool. It mentions the domain (arithmetic) and category (mathematical_constants), but gives no explicit comparison to alternatives like 'compute_e_series' or 'e' (which appears to be a different tool). There's no guidance on appropriate n values, convergence considerations, or when to choose this method over other e-computation approaches.

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