get_relational_entity_metadata

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

No annotations are provided, so the description alone must convey behavioral traits. It describes a read operation but does not disclose potential side effects, permissions required, rate limits, or how missing identifiers are handled. The lack of detail is insufficient for full transparency.

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 sentences that are front-loaded with the tool's purpose and value. Every sentence adds meaning; no redundant or filler content. Ideal length for quick comprehension.

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 lack of an output schema and moderate complexity, the description covers the key return items (columns, types, mappings, ETL capabilities). It could be slightly more explicit about the output format (e.g., JSON), but overall it provides sufficient context for its straightforward metadata retrieval purpose.

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 input schema covers all three parameters with descriptions (100% coverage). The description adds context about the returned data but does not significantly enhance parameter semantics beyond what the schema already provides. Baseline score of 3 is appropriate.

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 gets detailed metadata for a specific relational entity, listing concrete details like column definitions, data types, SQL type mappings, and ETL extraction capabilities. It distinguishes itself from siblings by emphasizing optimization for data warehouse loading and transformation workflows.

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 mentions it is 'optimized for data warehouse loading and transformation workflows,' which implies a use case but does not explicitly state when to use this tool versus alternatives like 'get_relational_metadata' or 'get_table_schema'. No exclusion or alternative guidance is provided.

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