Get Backtest By Stat Type

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

Annotations cover read-only, idempotent, open-world safety. The description adds the auth requirement and confirms the return content (hit rate and profit). No contradictions. This is adequate but not rich beyond the annotations.

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, front-loaded with the core output and breakdown dimension, followed by a direct usage hint. No wasted words.

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 read-only backtest tool with no output schema, the description adequately explains what is returned and the auth requirement. It could specify whether the breakdown is a list or a mapping, but the core information is present.

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 from, to, and league (with enum). The description mentions 'stat market' but does not document any parameter. Baseline 3 is appropriate when the schema does the heavy lifting.

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?

States a specific verb and resource: backtest metrics (hit rate, profit) broken down by stat market. Distinguishes itself from siblings like proplab_backtest_summary and proplab_backtest_by_rating by naming the breakdown dimension.

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?

Gives a clear use case: find which markets the model performs best on. However, it does not provide explicit when-not-to-use guidance or suggest alternatives for other backtest breakdowns (e.g., by rating vs by stat).

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