power_series_sum

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 states the calculation but does not mention potential issues like overflow for large n, handling of non-integer x, or error conditions. For a mathematical tool with no annotation coverage, this lack of behavioral details 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 highly concise and front-loaded, with the core purpose stated in the first sentence and additional context efficiently added in parentheses. Every word contributes to understanding, with no redundant or verbose elements.

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 mathematical nature, 2 parameters, no annotations, and no output schema, the description is minimally adequate. It covers the basic purpose and parameter roles but lacks details on behavior, constraints, or return format, which are important for a calculation tool.

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 description adds meaningful context beyond the input schema, which has 0% description coverage. It explains that x is the base and n is the exponent limit in the series, clarifying the mathematical roles. However, it does not specify constraints (e.g., n must be non-negative) or examples, leaving some semantic gaps.

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 explicitly states the tool's purpose with a specific mathematical formula: 'Calculate the sum of a power series: x⁰ + x¹ + x² + ... + xⁿ for given x and n.' It clearly distinguishes this from sibling tools like 'series_sum' or 'geometric_sum' by specifying the exact power series structure, avoiding ambiguity.

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 includes a domain and category ('Domain: arithmetic, Category: general'), which provides some implied context for when to use this tool. However, it does not explicitly state when to choose this over alternatives like 'geometric_sum' or 'series_sum', nor does it mention any prerequisites or exclusions, leaving usage guidance incomplete.

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