pi_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', which hints at computational complexity or accuracy, but doesn't specify performance characteristics, error handling, output format, or limitations (e.g., maximum precision). For a tool with no annotations, this leaves significant gaps in understanding how it behaves.

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 and front-loaded, with the core purpose stated in the first sentence. The additional domain and category information in parentheses is brief and doesn't detract from clarity. There's no wasted text, making it efficient for an agent to 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?

Given the tool's complexity (mathematical computation with precision), lack of annotations, no output schema, and low schema coverage, the description is incomplete. It doesn't explain what the output looks like (e.g., string of digits, truncation/rounding), error conditions, or performance implications. For a tool that could have nuanced behavior, this leaves too much unspecified.

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 1 parameter ('precision') with 0% description coverage, so the description must compensate. It adds meaning by specifying that 'precision' refers to 'pi digits' generation, but doesn't clarify units (e.g., decimal places), valid ranges, or default values. This provides some context but falls short of fully documenting the parameter's semantics.

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 pi digits to specified precision using high-precision arithmetic.' It specifies the verb ('Generate'), resource ('pi digits'), and method ('high-precision arithmetic'), making it easy to understand what the tool does. However, it doesn't explicitly differentiate from sibling tools like 'pi' or 'compute_pi_chudnovsky', which likely serve similar mathematical constant purposes.

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 ('arithmetic') and category ('mathematical_constants'), but this is too vague to help an agent choose between many sibling tools (e.g., 'pi', 'compute_pi_chudnovsky', 'e_digits'). There are no explicit instructions on use cases, prerequisites, or comparisons to other tools.

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