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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint as false, so the agent knows this is a safe, non-mutating operation. The description adds a price tag ($0.08 per dataset), which is useful cost context, but doesn't elaborate on how validation behaves or whether it modifies the input. No contradiction with annotations, and the description adds some value beyond them, hence a 3.

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 plus a price note. The purpose and usage are front-loaded, and there is no redundancy. The price is a useful addition for cost-aware agents, and the description is efficiently structured.

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?

With four parameters and zero schema coverage, the description is incomplete. It doesn't explain what format the 'data' string should be (raw CSV text? JSON string?), how to pass it, what the output looks like, or how validation handles errors. The output schema exists but is not referenced. For an agent to call this correctly, it would need to guess at parameter semantics.

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 0%, so the description must explain the parameters. It mentions operations like 'deduplicate' but doesn't map them to the 'deduplicateBy' parameter or explain 'requiredColumns'. The only inference is that these operations exist, but the agent cannot know how to configure them. This is a significant gap.

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 normalizes, trims, validates, and deduplicates tabular CSV or JSON data. It names the specific operations and data types, which distinguishes it from general validators like document_validator. However, it doesn't explicitly contrast with sibling tools, so it falls short of a 5.

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 a use condition: 'Use when JSON or CSV-like data needs normalization, trimming, or duplicate removal.' This gives clear context for when to invoke the tool. But it doesn't mention when NOT to use it or suggest alternatives, so it's only minimally adequate.

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