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 says nothing about header handling, whether sorting is stable, what happens with non-numeric values in numeric mode, how the delimiter is inferred, or what the tool returns — significant gaps for a data-transformation tool.

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 with no filler; the core action and the mode options come first. It is efficient, though its terseness contributes to the gaps in other dimensions.

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 no annotations, no output schema, and 0% parameter description coverage for a 5-parameter mutation-style tool, the description is too thin. An agent cannot determine delimiter behavior, direction defaults, or header handling from the definition alone.

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% across 5 parameters. The description only loosely covers 'column' and 'mode' (alpha/numeric) and says nothing about 'delimiter', 'direction' (asc/desc), or the 'input' format, leaving half the parameters undocumented in both schema and prose.

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 states a specific verb (sort) and resource (CSV rows) with the key constraint 'by one column' and hints at the mode dimension (alpha or numeric). It clearly distinguishes from unrelated siblings like csv_filter or csv_statistics, though it doesn't explicitly name a sibling to route 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 statement of when to use this over alternatives such as csv_filter or csv_to_json, and no prerequisites or conditions. The only usage signal is implicit: if you need sorted CSV rows.

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