spss_import_csv

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

With no annotations, the description carries the full burden of transparency. It discloses that the tool creates a .sav file, where it saves by default, and that it bypasses the SPSS engine. However, it omits important behavioral traits such as whether existing files are overwritten, data type handling, or encoding limitations. This is adequate but not deeply transparent.

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 three sentences, front-loaded with the core purpose, and every sentence adds value: what it does, why it's faster, and where output goes. No redundant or filler text. It is succinct and well-structured.

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 tool's moderate complexity (5 params, no annotations), the description provides the essential context for the primary use case but leaves out guidance on several parameters (encoding, delimiter, column_labels) and potential edge cases like overwriting or unsupported features. It is sufficient for a straightforward conversion task but lacks depth for full autonomous use without schema 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%, so the description must compensate for parameter understanding. It only mentions 'output_path' as a custom destination; it does not explain 'encoding', 'delimiter', or 'column_labels', even though these are important for correctly importing a CSV. The parameter names are somewhat self-explanatory, but the description adds minimal value beyond the schema.

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 uses a specific verb and resource: 'Convert a CSV file to SPSS .sav format'. It clearly differentiates from sibling analysis tools by naming the conversion goal and the technical approach (pandas + pyreadstat), and contrasts with SPSS syntax execution via spss_run_syntax. This leaves no ambiguity about what the tool does.

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 the primary use case: converting CSV to SPSS .sav without requiring SPSS installation. It explicitly compares to 'going through SPSS syntax' and notes it is 'much faster', providing an alternative. However, it does not state when not to use this tool or mention any prerequisites beyond the CSV file, so it is slightly short of a perfect score.

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