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

No annotations are provided, so the description carries the full behavioral burden. It discloses only that the result is a 'tidy CSV'; it never defines what 'clean' or 'dedupe' mean operationally (which columns key the dedupe, how nulls/whitespace/encodings are handled), nor whether the input is mutated in place. For a transformation tool with zero annotation coverage this is a meaningful gap.

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?

A single front-loaded sentence that names the operations first and the return value second, with no filler.

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 zero declared parameters and no output schema, the description is the only place where input provenance and result format could be explained. It never says how the CSV is supplied or retrieved, nor what a 'tidy' output actually looks like, so an agent cannot invoke it correctly with confidence.

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 schema declares zero properties, so there are no parameter semantics for the description to add or omit. Baseline 4 applies for a parameterless tool.

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?

States a concrete set of transformations (clean, dedupe, normalize) applied to a named resource (CSV) plus the output shape ('tidy CSV'). It is clear on its own, but gives no differentiation from any sibling — though the sibling list contains no other CSV tool, so there is little to differentiate against.

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?

There is no guidance on when to use this tool versus another approach, no prerequisites, and no exclusions. The agent must infer that it should reach for this whenever a CSV needs tidying.

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