get_table_schema

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

Annotations already declare readOnlyHint=true and openWorldHint=true, so the safety profile is covered. The description adds useful behavioral context — that it prevents column-name guessing and reveals semantic aliasing like brand→`designer` — but says nothing about error behavior for an invalid table alias or how table aliases are discovered beyond a pointer to list_tables.

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?

Front-loaded with the purpose, followed by routing guidance, then a concrete example, then arg notes — a sound ordering. The Rolex example partially restates the preceding sentence's point about `usd_price_decimal`, so it is slightly longer than strictly necessary, but each block still 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?

The return shape is handled by the output schema, and the description covers the remaining needs for a one-parameter read tool: when to call it, what it reveals, how to find valid aliases, and alias disambiguation. Nothing an agent needs in order to invoke it correctly is missing.

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% (the lone column is just typed 'string' with no description), so the description must carry the load and it largely does: it explains that `table` is a table alias, points to list_tables for the full set, and disambiguates the confusable 'gems' vs 'jewelry' aliases. Only the alias syntax/format itself is left implicit.

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 a table's column names and types' — and immediately frames the outcome ('so you can build a precise query'), which separates it from query_table, market_stats, and the other siblings. An agent knows exactly what this returns without opening the 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?

Explicitly prescribes when to call it: 'before query_table (or before adding filters to market_stats / price_trend)'. It names the alternatives and the exact condition that selects this tool, including a concrete worked example with a real table alias and field names.

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