df_list_relationships

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds no behavioral details such as pagination behavior, caching semantics, or return shape, but it does not contradict the annotations. It provides only minimal context beyond the annotations, so a mid-range score is appropriate.

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 short, front-loaded with the core action, and contains no filler. The second sentence about relationship_type adds a small but possibly useful detail. It earns its place, though it could have been integrated more clearly with the schema context.

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 8 parameters, no output schema, and no explanation of pagination, caching defaults, optional filters, or what the returned relationship objects look like. The description is sufficient to understand the intent but incomplete for an agent to confidently call the tool with the right parameters and interpret results.

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 only 25%, covering just project_id and version_id. The description mentions the fact-table-to-dimension-group join concept, which loosely maps to fact_table_id and dimension_group_id, but it does not explain page, page_size, language, use_cache, or the filtering semantics. With low schema coverage, the description should compensate, and it does not.

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 and resource ('List star-schema relationships') and clarifies the domain ('fact table to dimension group joins'), which distinguishes it from singular operations like df_get_relationship. It does not explicitly name sibling alternatives, but the purpose is clear and not tautological.

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?

No guidance is given about when to use this tool versus alternatives such as df_get_relationship, df_write_relationship, or df_list_dimension_groups. The context is limited to what the tool does; there are no exclusions, prerequisites, or conditions that would help an agent choose between listing and singular relationship operations.

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