twilize

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

With no annotations provided, the description carries full burden and adds valuable behavioral context: it discloses the type inference mechanism, the dependency requirement (tableauhyperapi), and the output format (.hyper file for Tableau). However, it does not mention potential side effects like file overwriting or performance considerations for large files.

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 well-structured and front-loaded with the core purpose, followed by implementation details, dependencies, parameter explanations, and return value—all in concise sentences that earn their place without redundancy.

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 complexity (file conversion with type inference), no annotations, and an output schema that handles return values, the description is complete: it covers purpose, dependencies, all parameters, and the confirmation output, leaving no gaps for the agent to understand and invoke the tool correctly.

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 description adds significant meaning beyond the input schema, which has 0% description coverage. It clearly explains the purpose of all four parameters (csv_path as source, hyper_path as output, table_name for internal naming, sample_rows for type inference), compensating fully for the schema's lack of documentation.

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 specific action ('Convert a CSV file to a Tableau Hyper extract'), the resource involved (CSV file to .hyper file), and distinguishes it from sibling tools like 'csv_to_dashboard' or 'hyper_to_dashboard' by focusing on file format conversion rather than dashboard creation or inspection.

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 context through the mention of Tableau workbooks and type inference, but does not explicitly state when to use this tool versus alternatives like 'csv_to_dashboard' or 'inspect_csv'. It provides a prerequisite ('Requires tableauhyperapi') but lacks explicit guidance on tool selection.

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