list_data_projects

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

With no annotations, the description must carry the behavioral burden; it does convey that this is a read-only listing and explains the filter matching rules (case-insensitive substring over name or description). It omits ordering, result limits/pagination, and what happens with no matches, which matter for an unpaginated-looking list call.

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?

Two short blocks, front-loaded with the purpose followed by filter semantics, with zero filler. Every clause either identifies the resource or constrains a parameter.

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?

An output schema exists, so return-shape detail is unnecessary, and the tool has only two optional params that are well covered. The main residual gap is list behavior at scale (ordering, caps, empty results), which is not addressed.

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 description coverage is 0%, so the description has to compensate, and it largely does: it defines name_filter's matching semantics (case-insensitive substring across name or description) and pins operation_type to "Import" or "Export". It does not say whether operation_type is case-sensitive or what an empty default yields.

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?

States a specific verb and resource ("List existing DMF data projects") and enumerates what each entry contains (name, Import/Export, description). That is enough for an agent to distinguish it from siblings such as create_data_project or list_project_entities without opening the schema.

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?

"Use the names with import_data / export_data" gives an explicit downstream workflow that positions this as a prerequisite discovery call. It does not name a when-not case or an alternative listing tool, which keeps it out of 5 territory.

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