twilize

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

With no annotations provided, the description carries the full burden and does well by disclosing key behavioral traits: it describes an end-to-end pipeline, mentions external dependencies, notes that password is used only for schema inference, and specifies default values and output format. However, it lacks details on error handling or performance limits.

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 with a clear overview followed by detailed sections for Args and Returns. It is appropriately sized for a complex tool, but the pipeline list could be more concise, and some parameter explanations are slightly verbose.

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?

For a complex tool with 13 parameters, no annotations, and an output schema, the description is largely complete: it explains the tool's purpose, pipeline, prerequisites, parameters, and return value. The output schema handles return details, but the description could better address error cases or limitations.

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?

Given 0% schema description coverage and 13 parameters, the description compensates by explaining most parameters in the 'Args' section, adding meaning like default behaviors and usage notes (e.g., username ignored if trusted_connection=True). It covers all required parameters and many optional ones, though some like theme and rules_yaml remain brief.

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 purpose with specific verbs ('Build a Tableau dashboard') and resources ('from a Microsoft SQL Server table'), and it distinguishes itself from siblings like csv_to_dashboard and mysql_to_dashboard by specifying the MSSQL source. The pipeline overview adds detail without redundancy.

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 clear context for when to use this tool (for building dashboards from MSSQL tables) and mentions prerequisites (pyodbc, ODBC Driver 17), but it does not explicitly state when not to use it or name specific alternatives among siblings, such as csv_to_dashboard for non-SQL sources.

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