calculate_information_ratio

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

The description discloses the core calculation and purpose. However, with no annotations, it does not cover edge cases (e.g., tracking_error of zero), error handling, or any behavioral constraints beyond the basic formula.

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?

Two sentences, no wasted words. The formula and purpose are front-loaded, making it easy for an agent to quickly understand the tool.

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?

For a simple mathematical tool, the description is minimal. It lacks parameter details, usage context, and behavioral transparency. Output schema exists but is not shown; however, the description does not leverage that to reduce burden. Given the sibling tool family, more completeness is expected.

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%, so the description must compensate. While parameter names (portfolio_return, benchmark_return, tracking_error) are somewhat self-explanatory, the description does not define them or specify expected units/format, which is insufficient given no schema descriptions.

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 calculates Information Ratio using the formula Active Return / Tracking Error and measures consistency of outperformance vs benchmark. It is specific but does not differentiate from sibling ratio tools like Sharpe or Treynor, which could confuse an agent.

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 on when to use this tool versus alternatives (e.g., Sharpe ratio, Treynor ratio). The description lacks context on prerequisites, typical scenarios, or exclusions.

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