get_extractor_fields

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

No annotations are provided. The description indicates a read-only operation (get) without side effects. However, it does not disclose any limitations, authentication requirements, or response characteristics beyond field names.

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?

A single, clear sentence that effectively conveys purpose and context. No extraneous information, though a bit more structure (e.g., bullet points) could improve scanability.

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 tool has no output schema, and the description does not explain the return format (e.g., array of strings, object). While adequate for a simple metadata tool, agents might need more detail on what the response contains.

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 100% with one required parameter. The description adds value by noting case-sensitivity and listing example entity names, which the schema only partially illustrates. Goes beyond the baseline of 3.

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 case-sensitive column/field names for 53 OData v4 extractor entities, with examples. It differentiates from sibling tools like query_dmc_extractor by being a metadata helper.

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 use for constructing valid query filters, but does not explicitly state when to use this tool vs alternatives (e.g., when field names are unknown) or when not to use it. Lacks clear context.

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