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

The description adds behavioral context beyond the annotations by explicitly stating that invalid rows are dropped and reported rather than causing failure. This complements the readOnlyHint and idempotentHint annotations, which already indicate safe, non-destructive operation.

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 exceptionally concise—two sentences that front-load the main action and include necessary details about validation behavior. Every sentence adds value.

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 tool has only one parameter and no output schema. The description covers input validation, thresholds, and error handling. It does not describe the output format, but given the simplicity of the tool and the presence of annotations, the description is nearly complete.

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 description is not required to explain parameters. However, it provides additional value by specifying the default thresholds (|log2FC|>=1, p<=0.05) used in the computation, which are not in the schema.

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 uses specific verbs ('Validate', 'compute') and clearly states the resource ('differential-expression table') and outputs ('-log10(p)', counts). It distinctly positions the tool for volcano plot data preparation, differentiating it from siblings.

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 explains when to use the tool (to prepare data for volcano plot visualization) and what it does, but does not explicitly state when not to use or mention alternatives. However, the sibling list contains no similar volcano-related tools, so the context is clear.

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