get_table_fields

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

No annotations are provided, so the description carries the full burden for behavioral disclosure. It implies a read-only metadata fetch ('Get') and adds useful context that field IDs are required for later queries. However, it does not explicitly state whether this is a safe read operation, mention authorization requirements, or note return format/limitations, leaving important behavioral traits undisclosed.

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?

The description is two sentences, front-loaded with a clear purpose statement followed by a critical usage directive. Every word earns its place, with no filler or redundancy. This is exemplary conciseness for a simple tool.

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 well-documented parameter and no output schema, the description is complete: it states what it returns (field IDs, names, types), when to use it (before query_dataset), and why (filters/aggregations need field IDs). There are no obvious gaps given the tool's complexity.

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 schema already provides 100% coverage for the single parameter (table_id) with its own description ('The table ID (use list_tables to find it)'). The tool description adds minimal param-specific meaning beyond referencing the table context and the need for field IDs, so it does not elevate above the baseline of 3.

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 explicitly states 'Get field IDs, names, and types for a table' — a specific verb ('Get') with a clear resource ('field IDs, names, and types for a table'). This clearly distinguishes it from sibling tools like list_tables (which lists tables) and query_dataset (which queries data), making the purpose unambiguous.

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 gives explicit when-to-use guidance: 'You MUST call this before building query_dataset calls — field IDs are required for filters and aggregations.' This names a dependent tool and reason, providing clear context. However, it does not explicitly mention when not to use it or name alternatives, so it falls short of the full 'when/when-not/alternatives' bar.

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