td_get_params

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

With no annotations, the description does well by explaining the default behavior (non-default values for token efficiency), pagination (50 params per page), and the discover mode returning rich schema. It does not explicitly state read-only nature but infers it from 'get' semantics.

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 short opening sentence and an Args list. It is front-loaded with the primary purpose and avoids unnecessary verbosity, making it easy for an AI agent to parse.

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?

The description covers core functionality, pagination, and discovery mode well, but lacks specification of the return format (e.g., structure of response) and error handling. Given no output schema, these details would complete the picture for robust agent usage.

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 compensates by explaining each parameter's effect: names returns all values, pattern uses glob, discover enables rich output, page controls pagination. These add meaning beyond the schema's titles and types.

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 retrieves parameters from an operator, specifying that it returns only non-default values by default. This is distinct from sibling tools like td_set_params (set) and td_get_op_info (operator info), providing a clear verb+resource identity.

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 includes guidance for the discover parameter to explore unfamiliar operators, but does not provide explicit when-to-use or when-to-avoid comparisons with sibling tools like td_get_op_info. This leaves some ambiguity for an AI agent to decide between tools.

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