describe_table

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It does reveal what the tool returns (columns, types, PKs, sample rows) and the 'all tables' option, but it does not state read-only semantics, potential performance implications of sample rows, or any limitations. This is adequate but not rich in behavioral detail.

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?

A single, tightly worded sentence that leads with the action and resource, then lists the specific details returned. No filler or redundancy — every word earns its place.

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?

For a tool with one optional parameter, no output schema, and clear siblings, the description covers the essential information: what it does, what it returns, and the 'one or all' scope. It could mention read-only nature or output format, but given the simplicity, it is nearly 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?

Schema description coverage is 100% and the schema already documents tableName with the exact 'Omit to describe all tables' guidance. The tool description adds no new parameter insight beyond restating this behavior, so it meets the baseline for full schema coverage without adding value.

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 ('Get') and lists concrete resources: column definitions, data types, primary keys, and sample rows. It clearly distinguishes from siblings: list_tables (just table names) and read_query (arbitrary SQL). An agent immediately understands this is for schema introspection.

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?

It states when to use the tool (when you need table structure and sample data) and covers both single and all-table cases via the 'one or all tables' phrasing. It does not explicitly say 'use list_tables for just names' or 'read_query for custom queries', but the purpose is clear enough that an agent can infer the right context.

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