airtable-user-mcp

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

Annotations indicate this is a non-readOnly, non-destructive, non-idempotent tool, which the description aligns with by implying creation (a write operation). The description adds significant behavioral context beyond annotations, such as support for computed fields not in the official API, detailed type options, and debug functionality, enhancing transparency about capabilities and constraints.

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 front-loaded with the core purpose but becomes lengthy with detailed lists and type options, which may be necessary but reduces conciseness. Some information, like the full breakdown of type options, could be structured more efficiently or referenced externally, making it somewhat verbose.

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 of 8 parameters, nested objects, and no output schema, the description is quite complete, covering field types, aliases, and type options in detail. However, it lacks explicit information on error handling, response format, or prerequisites, leaving minor gaps in full contextual understanding.

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?

Despite 100% schema description coverage, the description adds substantial value by elaborating on 'fieldType' with canonical names, friendly aliases, and normalization rules, and detailing 'typeOptions' with specific shapes per field type. This goes far beyond the schema's basic descriptions, providing essential semantic context for effective use.

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 the tool's purpose: 'Create a new field in an Airtable table.' It distinguishes itself from siblings like 'create_formula_field' by specifying it supports 'all field types including computed fields (formula, rollup, lookup, count) that are not available via the official API,' making it clear this is a comprehensive field creation tool.

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 provides clear context for usage by detailing supported field types and aliases, which helps users understand when to use this tool. However, it does not explicitly state when to use alternatives like 'create_formula_field' or 'update_field_config,' leaving some ambiguity in sibling differentiation.

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