csv_stats

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

No annotations are provided, so the description carries the burden of behavioral disclosure. It specifies the types of aggregates computed (numeric and categorical) and implies a read-only analysis. It does not mention edge cases or side effects, but the description adds meaningful behavioral detail beyond the schema.

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 two sentences long and front-loaded with the core purpose. Every word adds value, and the list of statistics is precise without unnecessary fluff.

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 3 parameters and no output schema. The description clearly communicates the tool's role and the types of statistics returned, but it does not explicitly state the return format (e.g., JSON object). Given the tool's simplicity and clear purpose, this is a minor gap.

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 100%, so the baseline is 3. The description does not add any additional meaning beyond what the schema already provides for parameters like 'file', 'fields', and 'maxRecords'. It does not elaborate on default behaviors or formatting.

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's function: 'Collect aggregate statistics for fields in a CSV file.' It specifies the exact statistics (min/max, mean, median, stdDev, top values) and distinguishes it from sibling tools like csv_inspect or csv_filter, which serve different purposes.

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 implies usage by describing what the tool does, but it does not explicitly state when to use it versus alternatives, nor does it mention exclusions. An agent can infer that this is for summary statistics, but explicit guidance is absent.

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