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

No annotations are provided, so the description carries full behavioral burden. The only extra info is the cost ($0.10) which is useful. It doesn't state whether the operation is read-only, what permissions are needed, or what a backtest entails (data source, latency, output format).

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 short sentences; the purpose is front-loaded and the price is appended. No filler. It could be more useful but isn't bloated.

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?

A tool with 4 params, a nested allocation object, no annotations, and no output schema. The description omits return values, backtest methodology, data scope, and how results are shaped — significant gaps for a costly simulation 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?

Schema coverage is 100%, so the schema fully documents all four parameters with descriptions and enums. The description adds little parameter-level meaning beyond pointing at the benchmark by name. Baseline 3 is appropriate given full coverage.

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 verb and resource (backtest a stock strategy over multiple years against a named benchmark). However, 'evaluate_tsunami_strategy' and 'Stock Bloc's high-growth watchlist benchmark' are jargon that don't clarify the tool's core function well, and it doesn't clearly distinguish from the sibling run_quant_simulation.

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 explicit guidance on when to use this vs run_quant_simulation, which appears to be the closest sibling. The agent is left to infer the boundary between 'evaluate strategy' and 'run quant simulation'.

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