get_table_schema

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

Annotations already declare readOnly/idempotent/non-destructive, so the bar is lower, yet the description adds real behavioral context: it is free and scans no data (cost profile), partitioning=null means every query reads the whole table, and nested columns appear as dotted paths flagged `repeated` to signal UNNEST needs.

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 one-line summary, then two tightly scoped bullets that each teach a distinct query-writing consequence, then an Args block. No filler sentences; every clause changes how the agent behaves.

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?

No output schema exists, so the description must convey returns — and it names all four returned facets (columns, partitioning, size, freshness) plus the `repeated` flag semantics. Nothing an agent needs to call and interpret this tool 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 description coverage is 0%, so the description carries the full burden, and it does: dataset_id ('events_raw'), table_id (table or view name), and environment (which configured BigQuery environment, omit for default, see list_environments). Every parameter gets meaning and an example.

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?

Opens with a specific verb and resource plus the exact payload: 'Get a table's columns, partitioning, size and freshness.' This distinguishes it cleanly from siblings like list_tables (enumerates) and check_table_freshness (freshness only), so an agent can route without opening any 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 states when to call it ('Call this before writing a query') and why, and points to list_environments for discovering valid environment values. It lacks an explicit when-not / alternative comparison against check_table_freshness, but the pre-query positioning is clear guidance.

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