list_schemas

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

No annotations are provided, so the description carries the disclosure burden. It does describe the accessibility filter and the two returned aggregates, but says nothing about permission requirements or whether results are paginated or cached. Adequate for a zero-parameter read, but not rich.

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 sentences: the first defines output and scope, the second gives the usage trigger. Zero filler and front-loaded.

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 values need not be re-explained, and the description covers scope plus the recommended call order. Only the absence of any permission/access caveat keeps it from fully complete.

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 tool takes no parameters, so there is nothing to disambiguate; baseline 4 applies. The description correctly does not waste space on parameter semantics.

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 all accessible schemas/data partitions') and adds the returned fields (table count, total size), which distinguishes it from siblings like list_tables and search_metadata. An agent can tell immediately what this tool returns.

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 says to call it first when exploring an unfamiliar database, which is a clear contextual trigger. It stops short of naming alternatives (e.g. list_tables or describe_table) for enumerating objects, so routing advice is slightly incomplete.

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