get_schema

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

No annotations are provided, so the description fully bears the burden. It clearly states the tool is read-only (introspect) and lists what it returns, including RLS policies. There is no mention of side effects, which is appropriate for an introspection tool.

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, no wasted words. It front-loads the action and quickly explains when to use it. 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?

The description lists the key parts of the schema output (tables, columns, etc.), which is adequate for most use cases. However, without an output schema, it could be slightly more precise about the return structure (e.g., list of tables with nested columns). Still, it is reasonably 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?

With 100% schema coverage, the parameter is already fully described in the input schema. The description adds no additional meaning beyond what the schema provides, so the 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 uses specific verbs ('introspect') and resources ('database schema') and clearly enumerates what is included (tables, columns, types, constraints, RLS policies). This distinguishes it from sibling tools like run_sql or rest_query, which execute queries rather than inspect schema.

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 advises using the tool 'before writing queries', which provides clear usage context. However, it does not explicitly exclude cases (e.g., when you need to actually query data) or mention alternatives, so it scores slightly below a perfect 5.

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