get_metadata_catalog

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

With no annotations, the description warns about potential slowness for large databases, a key behavioral trait. It also implies a full return scope. Slight lack of detail on output structure, but sufficient for 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?

Three concise, front-loaded sentences covering purpose, usage, and warning with no redundancy. Every sentence adds value.

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 returns a full metadata catalog with no output schema or parameter details, the description provides essential context (when to use, performance) but lacks specifics on return structure or exact behavior.

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 coverage is 0% for the sole parameter 'datasource_name'. The description implies it identifies the data source but does not explain format or constraints. Partial compensation but not detailed.

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 uses specific verb 'Get' and resource 'FULL metadata catalog (all databases, schemas, tables)', clearly distinguishing its broad scope from sibling tools like search_tables.

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?

Explicitly states when to use ('When starting with a data source') and when to prefer an alternative ('prefer search_tables for targeted queries'), providing clear context and exclusions.

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