create_field

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

Annotations are neutral (readOnlyHint=false, destructiveHint=false). The description adds value by mentioning that computed fields use the internal API, which is a behavioral trait. It also explains the debug parameter for diagnostics. However, it does not detail side effects, reversibility, or auth requirements beyond the default.

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 long but well-structured with labeled sections (FIELD TYPES, TYPE OPTIONS). It is front-loaded with the main purpose. While verbose, each section adds necessary detail; could be slightly more concise but maintains clarity.

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?

Given the complexity (8 parameters, nested typeOptions, many field types), the description is comprehensive. It covers all parameter semantics and behavioral notes. However, it lacks an explicit statement about return value or output format, though the debug parameter hints at raw response.

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?

Input schema covers 100% of parameters with descriptions. The description significantly adds meaning by detailing fieldType aliases (e.g., 'url' maps to type 'text' with validator) and providing complete typeOptions shapes for each field type (formula, rollup, lookup, etc.). This goes far beyond the schema alone.

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 clearly states 'Create a new field in an Airtable table. Supports all field types including computed fields...' This specifies the verb (create), resource (field in Airtable table), and distinguishes it from siblings like update_field_config or create_formula_field by highlighting support for computed fields not available in the official API.

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 implies usage when creating any field type, especially computed fields. However, it does not explicitly state when not to use this tool (e.g., when a simpler operation like create_formula_field suffices) or provide alternative tools. The sibling create_formula_field exists but is not differentiated.

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