e_digits

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions 'high-precision arithmetic', hinting at computational intensity, but fails to detail critical aspects: performance expectations (e.g., time/complexity for high precision), error handling (e.g., invalid precision values), or output format (e.g., string vs. number). For a tool with no annotations, this leaves significant gaps in understanding its 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?

The description is extremely concise and front-loaded, with no wasted words. The first sentence directly states the tool's function, and the parenthetical adds domain context efficiently. Every part earns its place, making it easy to parse quickly without unnecessary elaboration.

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 the tool's complexity (mathematical constant generation with precision control), lack of annotations, and no output schema, the description is insufficient. It doesn't explain the return value (e.g., a string of digits, a number), error conditions, or performance implications. For a tool that likely involves computational trade-offs, more context is needed to use it effectively, resulting in a low score.

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 input schema has one parameter ('precision') with 0% description coverage, so the description must compensate. It adds meaning by specifying that precision controls the generation of 'e digits', implying it determines the number of decimal places or digits output. However, it doesn't clarify units (e.g., decimal places vs. total digits), valid ranges, or default behavior, leaving some ambiguity. Given the low schema coverage, this is a minimal but adequate explanation.

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's purpose: 'Generate e digits to specified precision using high-precision arithmetic.' It specifies the verb ('Generate'), resource ('e digits'), and method ('high-precision arithmetic'), making the function unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'e' or 'compute_e_series', which could provide similar functionality, preventing a perfect score.

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 no guidance on when to use this tool versus alternatives. It mentions the domain and category ('Domain: arithmetic, Category: mathematical_constants'), but this is generic and doesn't help distinguish it from siblings like 'e' or 'compute_e_series'. There are no explicit instructions on prerequisites, limitations, or scenarios favoring this tool over others.

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