quant_backtest_method

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

Annotations already indicate readOnlyHint=true and idempotentHint=true. The description adds significant behavioral context: no separate backtest implementation, costs applied one-way, and the warning about survivorship bias. This goes beyond the annotations and is highly transparent.

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 concise and well-structured: a one-line summary followed by behavioral details, then clear 'Args' and 'Returns' sections. Every sentence adds value without redundancy, and the structure aids quick scanning.

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 tool's purpose, mechanics, parameters, return format, and important caveats (survivorship bias, cost estimates). Given the tool has a single complex parameter and an output schema, the description is complete and leaves no critical gaps.

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 input schema includes descriptions for all parameters, and the tool description's 'Args' section lists them. The body adds meaning for 'period' (intraday cap) and 'top_n' (xs_momentum only), enhancing understanding beyond schema defaults. Schema coverage is formally 0% but descriptions exist, so baseline is 3 and the added context raises it.

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: 'Backtest a registered method by replaying its own analyze() over history.' It uses a specific verb and resource, and the details (bar-by-bar replay, daily vs intraday) distinguish it from sibling tools like quant_describe_method or quant_list_methods.

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 context on when to use the tool by explaining its mechanics (daily bar filling, intraday caps) and includes a caution to treat results as parameter validation. However, it does not explicitly state when not to use it or compare to alternatives, though the uniqueness of the tool makes it clear.

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