metadata_list_schemas

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

No annotations provided, so description carries full burden. It does not disclose behavioral traits like read-only nature, authentication requirements, or return format. The description is too minimal to inform agent behavior beyond the obvious.

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 one short, front-loaded sentence. It is concise but could benefit from more detail without sacrificing brevity. Good structure.

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 simple parameters and no output schema, the description should explain what a schema is or what output to expect. It does not. The tool is straightforward but the description lacks sufficient context for an agent to fully understand its 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 100%, so baseline is 3. The description adds no new meaning beyond the schema (which already includes an example). However, it does tie the parameter to the tool's purpose (for a specific dataset). No improvement.

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 a specific verb 'List' and resource 'available data schemas for a specific dataset'. It clearly distinguishes from sibling tools like metadata_list_datasets and metadata_list_fields by focusing on schemas. High purpose clarity.

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 implies use when needing schemas for a dataset, but it lacks explicit guidance on when to use this tool versus alternatives (e.g., metadata_list_fields). No exclusions or prerequisites mentioned. Adequate but not strong.

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