spss_import_csv

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It usefully reveals that conversion happens directly via pandas + pyreadstat, bypasses the SPSS engine, saves next to the CSV by default, and supports a custom output_path. This is meaningful behavioral context beyond the schema, though it does not describe overwrite behavior or type inference.

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?

Three concise sentences with no filler. The core purpose is front-loaded, then practical benefits (no SPSS installation, speed) and default output behavior follow. Every sentence earns its place.

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 the output schema and fully described parameters, the description is sufficient for an agent to invoke the tool correctly. It covers the essential conversion behavior, performance characteristics, and output destination. Minor omissions such as overwrite behavior or variable type handling are acceptable because the structured schema already handles parameter details.

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 input schema already documents all five parameters. The description adds a little extra meaning by emphasizing the default output location next to the CSV and the custom output_path option, but it does not go beyond what the schema already provides. This matches the baseline for high schema coverage.

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 a specific action ('Convert a CSV file to SPSS .sav format'), identifies the resource (CSV) and output target (.sav), and distinguishes from sibling tools by naming the underlying method. It also explicitly contrasts itself with SPSS syntax, helping an agent recognize this as the dedicated import/export conversion 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 provides strong usage context: it says to use this tool for CSV-to-SAV conversion without requiring IBM SPSS Statistics, and explains that it is faster than going through SPSS syntax. It doesn't explicitly list when not to use it or compare it to related tools like spss_run_syntax, but the guidance is clear enough for selection.

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