make_table_from_csv

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

No annotations provided, so description carries full burden. It describes the transformation (parse and render) and return value, but could more explicitly state that the tool is read-only or has no side effects. However, given the tool's nature, this is adequate.

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 concise docstring with a one-sentence summary followed by parameter details. Every sentence is necessary, and the structure front-loads the core purpose.

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?

With 6 parameters (1 required) and an output schema present, the description covers all parameters and states the return value ('Formatted table'), making it complete for an agent to use.

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 coverage is 0%, but the description includes an Args section that explains every parameter (csv_text, delimiter, has_header, fmt, style, auto_format) with defaults and meaning, adding full 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 'Parse a CSV/TSV string and render as a table' uses a specific verb ('parse', 'render') and resource ('CSV/TSV string', 'table'), clearly distinguishing it from siblings like 'make_table_from_json' and 'make_table'.

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 with CSV/TSV strings but does not explicitly state when to use this tool versus alternatives (e.g., 'make_table_from_json') or provide 'when not to use' guidance.

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