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

The annotation readOnlyHint=true already signals a non-mutating operation, and the description does not contradict that. The description adds value by detailing what types of data sources are included (own DBs, REST, warehouses, public API catalog) and how the tool fits into the overall connection flow. This goes beyond the annotation without repeating it.

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 moderately long but every sentence earns its place: it lists categories, mentions the curated catalog, gives a use case, and provides flow context. The most important content (what is listed) is front-loaded. It could be slightly tightened, but it is efficient and well-organized for a tool with no parameters.

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 is a simple list operation with no parameters and a read-only annotation, the description is thorough: it specifies the exact scope of data sources, the intended use case, and related tools. It does not explain return format, but for a list tool with no schema this is acceptable; an agent can infer it returns a list of names/types. No critical information is missing.

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 tool has zero parameters, so there is nothing for the description to clarify. The schema is empty and fully covered by definition. The description explains the output content (list of data source types), which is more useful than any parameter detail. Baseline for 0 params is 4, and the description fully compensates by describing the result.

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 states a specific verb ('List') and a precise resource ('external DATA SOURCE types an app can connect to'), enumerating concrete examples (Postgres, REST API, warehouses) and a curated catalog. It clearly distinguishes itself from siblings like build_connect_data_source and build_discover_source by focusing on enumeration of available source types, and even references the flow to contextualize its role.

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?

It explicitly says when to use it: 'Read this to offer a connect your own data option.' It also gives the flow (build_connect_data_source → build_discover_source → build_bind_data_source) and points to build_get_skills for further info. However, it does not explicitly state when not to use it or mention alternative tools that might replace it, so it stops short of a 5.

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