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

With no annotations provided, the description carries the full burden. It reveals the output metrics, which is useful, but it does not disclose whether the operation is read-only, whether it has side effects, how the backtest is performed, or what assumptions it makes. This is minimal behavioral context for a tool with no annotation coverage.

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 a single, well-structured sentence that front-loads the action, defines the evaluation universe with the ticker list, and ends with the output metrics. Every element serves a purpose with no filler or redundancy.

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?

The description covers the purpose and return metrics, and the schema fully documents parameter values, giving an agent a reasonable starting point. However, with no output schema and no annotations, the tool would benefit from mentioning defaults (benchmark, horizon), allocation constraints, and metric interpretation. These are moderate gaps for a 4-parameter tool with a nested input.

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 100%, so the schema already documents all four parameters. The description adds context about the watchlist and output metrics, which helps interpret the allocation parameter, but it does not materially expand on parameter meanings beyond what the schema provides. The baseline 3 applies.

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 states a specific verb ('Evaluate') and a specific resource ('quantitative portfolio strategy against the Super Sonic Tsunami infrastructure watchlist') with the ticker list, and it names the output metrics (Alpha, Sharpe, Win Rate, Drawdown). This makes the tool's role clear, though it does not explicitly distinguish it from the sibling 'run_quant_simulation', which may also evaluate strategies.

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 gives no explicit guidance on when to use this tool versus alternatives like run_quant_simulation, and it does not mention exclusions or prerequisites. The only implicit signal is the watchlist keyword, which hints at the intended scenario but does not constitute real usage guidance.

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