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

The description adds meaningful behavioral context beyond the annotations. It specifies the types of validation performed (missing fields, prices, duplicates, platform readiness), which aligns with the non-destructive, idempotent nature declared by annotations. No contradictions.

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 a single, efficient sentence that front-loads the action and key details. Every element contributes to understanding, with no redundancy.

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 and validations, but it omits what the output or return value looks like. Since there is no output schema, an agent cannot know if the tool returns a report, errors, or a simple pass/fail. This is a gap for a tool performing complex validations.

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?

With 50% schema description coverage, the description enriches the meaning of the 'rows' parameter by listing expected fields (SKU, title, price, category, image) and validation dimensions. For the 'platform' parameter, the schema description is already clear. This adds significant value beyond the bare 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 clearly states the verb 'Validate' and the resource 'product rows', listing specific validation checks (missing fields, invalid prices, duplicate SKUs, platform readiness). However, it does not explicitly distinguish itself from sibling tools like 'duplicate_sku_finder' or 'csv_cleaner', which have overlapping functionality.

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 no guidance on when to use this tool versus alternatives. There is no mention of when-not-to-use or which sibling tools might be more appropriate for specific subtasks, such as duplicate SKU only validation.

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