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 action but does not describe any behavioral traits such as error handling, performance characteristics, or output format. For a tool with no annotations, this leaves significant gaps in understanding how the tool behaves beyond its basic function.

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, consisting of a single sentence that directly states the tool's purpose and parameters, followed by domain and category in parentheses. Every word earns its place, with no wasted information, making it highly 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 (a mathematical calculation with 3 parameters), no annotations, and no output schema, the description is incomplete. It lacks information on the output format, error conditions, or any contextual details needed for reliable use. The description does not compensate for the absence of structured data, leaving the agent with insufficient guidance.

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 lists the parameters ('first term, last term, and number of terms'), which adds meaning beyond the input schema that has 0% description coverage. However, it does not provide details on parameter constraints, units, or examples. With low schema coverage, the description compensates partially but not fully, warranting an average score.

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: 'Calculate the sum of an arithmetic series based on first term, last term, and number of terms.' It specifies the verb ('calculate'), resource ('sum of an arithmetic series'), and parameters. However, it does not explicitly differentiate from sibling tools like 'arithmetic_series' or 'arithmetic_sum', which appear related, so it falls short of 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 ('arithmetic') and category ('general'), but this does not help an agent choose between this and sibling tools such as 'arithmetic_series' or 'arithmetic_sum'. No explicit when-to-use or when-not-to-use instructions are included.

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