data_source_discovery

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

No annotations are present, so the description carries the burden. The verb 'List' implies a read-only operation, and 'configuration requirements' provides some behavioral context. However, it doesn't disclose authentication needs, pagination, or any limitations.

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 concise sentence that clearly states the tool's purpose. It is front-loaded and contains no redundant information.

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 is simple, but the description leaves the 'search' parameter unexplained and gives no usage guidance relative to siblings. Given the simple schema and lack of output schema, some gaps are acceptable, but the param gap makes it incomplete.

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 schema has one optional 'search' object with no description, and the description does not mention this parameter at all. At 0% schema description coverage, the description fails to compensate, leaving the parameter's purpose and format unclear.

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 lists available marketing data sources along with their configuration requirements. It distinguishes from sibling tools like accounts_discovery and field_discovery by focusing specifically on data sources.

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 when you need to see data sources, but it doesn't explicitly mention alternatives or when not to use this tool. No guidance is provided about how it relates to other discovery tools.

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