origin_list_fit_functions

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

With no annotations, the description carries full burden for behavioral disclosure. It states the tool lists names and parameters, implying a read-only operation, but does not confirm safety, idempotency, or side-effect-free behavior. The description provides basic transparency but lacks detail on state dependencies or data requirements.

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 single, clear sentence with no wasted words. Every part contributes to understanding the tool's function.

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 has zero parameters and an output schema exists, the description is mostly complete. However, it would benefit from clarifying what 'common' means (e.g., built-in functions only) or providing any usage context, though the output schema likely covers return details.

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 input schema has zero parameters (100% schema coverage automatically), so no parameter documentation is needed in the description. The description adds no param info because none exists; this is appropriate and complete.

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: 'List common Origin nonlinear fit function names and parameters.' It uses a specific verb ('List') and resource ('fit function names and parameters'), and distinguishes from sibling tools like origin_nonlinear_fit which perform actual fitting.

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 the tool is used to discover available fit functions before performing nonlinear fitting, but does not explicitly state when to use it versus alternatives like origin_nonlinear_fit or origin_nonlinear_fit_structured. No exclusions or when-not-to-use guidance is provided.

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