compute_pi_chudnovsky

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

No annotations are provided, so the description carries full burden. It states the algorithm and convergence trait but lacks critical behavioral details: required permissions, computational cost, output format (e.g., decimal string, rational approximation), error handling, or precision limits. For a computational tool with no annotations, this is a significant gap.

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—a single sentence with parenthetical domain/category. It front-loads the core purpose and algorithm, with zero redundant information. Every word earns its place, making it efficient for quick understanding.

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 annotations, 0% schema coverage, and no output schema, the description is incomplete. It lacks details on behavior, parameters, return values, and comparative usage with siblings. For a mathematical computation tool with one parameter, more context is needed to guide effective use.

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%, with one parameter 'terms' undocumented. The description adds no parameter semantics—it doesn't explain what 'terms' means (e.g., number of iterations, series terms affecting precision), valid ranges, or default behavior. With low coverage and no compensation, the score reflects inadequate parameter clarification.

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 pi using a specific algorithm (Chudnovsky) and mentions its key characteristic (extremely fast convergence). It distinguishes from siblings like compute_pi_leibniz, compute_pi_machin, and compute_pi_nilakantha by naming the algorithm, but doesn't explicitly differentiate performance or use cases beyond convergence speed.

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?

No guidance is provided on when to use this tool versus alternative pi-computation siblings. The description mentions 'extremely fast convergence' but doesn't explain practical implications (e.g., for high precision, fewer terms) or compare to other algorithms. Usage context is implied but not explicit.

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