summary_statistics

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

No annotations are provided, so the description must carry the full burden. It discloses that the operation is read-only, which is a key behavioral trait. However, it does not mention edge cases like what happens if the column contains non-numeric data, or whether missing values are handled, or if there are any prerequisites like the sheet existing. For a simple read-only tool, the read-only disclosure is a positive, but more context on expected behavior would improve transparency.

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 sentence with no wasted words. It front-loads the purpose, lists the computed statistics, and adds the read-only qualifier. Every phrase earns its place, and the structure is clear and efficient.

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?

Given that an output schema exists, the description does not need to explain return values. The tool is simple with three self-explanatory parameters. The description covers the core action and safety (read-only), which is sufficient for an agent to invoke it correctly. Minor gaps like handling of non-numeric columns are not critical for a basic summary statistics tool and are not essential for correct invocation.

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 input schema has zero description coverage, so the description must compensate. It mentions 'for a column in a workbook sheet,' which maps to the three parameters (file_path, sheet_name, column) and gives a sense of their roles. However, it does not explicitly explain that file_path is a path string, sheet_name is a sheet name, and column is a column identifier. The names are self-explanatory, but the description could be more explicit about the expected format or any constraints (e.g., column must be numeric). It provides minimal added value beyond the parameter names.

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 computes summary statistics for a column in a workbook sheet, and lists the specific statistics (count, missing, mean, median, standard deviation, min, max, quartiles). The verb 'Compute' and resource 'summary statistics for a column' are specific and distinct from siblings like rolling_average or correlation_matrix. The read-only note further distinguishes it as a non-mutating analysis tool.

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 does not explicitly state when to use this tool versus alternatives, nor does it mention any exclusions or alternatives. It only says 'Read-only,' which is a safety hint but not usage guidance. Without comparisons to siblings like data_quality_report or rolling_average, the agent has to infer when this is the right choice based on the purpose alone.

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