base_saveDDL

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

No annotations exist, so description carries full burden. It explains the operation (server-side save) and return type, but omits details like file overwrite behavior, directory creation, or required permissions. This leaves gaps for a mutation-like tool.

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 concise, with a clear header and bulleted argument list. Every sentence adds value, though the 'Returns' line is somewhat generic. No fluff, but could be slightly tighter.

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 4 parameters, no output schema, and no annotations, the description covers the core purpose, arguments, and return type adequately. It explains the tool's reason for existence (token limit). Minor gaps like error handling or file behavior prevent a 5.

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%, so description provides essential parameter meaning. It gives examples for database_name and object_name, specifies allowed values for object_type, and documents defaults for output_dir. This adds significant value beyond the schema's type-only definitions.

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 extracts DDL and saves to file, specifying the resource (Teradata object DDL) and action (save to .sql). It distinguishes from sibling tools like base_tableDDL by explaining it solves token limits, making purpose unambiguous.

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 explicitly addresses when to use—when DDL is large and would exceed token limits—and contrasts with inline alternatives. However, it lacks explicit statements about when not to use or direct references to sibling tools.

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