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

Annotations already declare readOnlyHint=true and destructiveHint=false, so safety is covered; the description adds substantial non-obvious behavior: calibration must use the mean control ΔCt rather than a single sample, and the engine auto-selects Welch t, Student t, or Mann-Whitney when within-group variance is zero. This is genuine algorithmic disclosure well 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?

The critical scoping and anti-hand-calculation warning is front-loaded, and the return-field list is appended compactly. Emojis and bold emphasis add noise but the sentences largely earn their place; it is somewhat dense but not padded.

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?

There is no output schema, but the description enumerates the return fields (fc, fold_values, p_value, stat_method, tested_variable, dct, significance, outlier_check) and stresses faithful relay of stat_method/tested_variable. For a read-only analysis tool, an agent has everything needed to call and report it correctly.

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 already documents each parameter. The description still adds value by stating that Ct values are comma-separated and that each group's target and reference values must correspond one-to-one, which clarifies alignment semantics beyond the raw field 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 names the exact computation (ΔCt, ΔΔCt, 2^-ΔΔCt relative expression/fold change plus between-group testing) and the expected inputs (target and reference Ct values for control/treatment groups). It is a specific verb+resource statement that an agent can match to a qPCR analysis request without opening the schema.

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?

It states mandatory usage ('必须走这个动作') whenever the agent is asked to compute ΔΔCt or fold change and perform group comparison, and explicitly forbids manual calculation. It does not name a sibling alternative, but no sibling competes for this exact task, so the guidance is clear though not comparative.

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