airtable-user-mcp

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

The description adds valuable behavioral context beyond annotations: it explains that validation helps 'catch errors early' before actual field operations, and describes the return value ('whether the formula is valid and what result type it produces'). While annotations already indicate read-only, non-destructive, and idempotent behavior, the description provides practical context about the tool's role in preventing errors in subsequent operations.

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 perfectly concise and front-loaded: the first sentence establishes the core purpose, the second explains the return value, and the third provides crucial usage guidance. Every sentence earns its place with no wasted words, making it easy for an agent to quickly understand the tool's role.

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 validation tool with comprehensive annotations and full schema coverage, the description provides excellent contextual completeness. It explains the tool's purpose, when to use it, and what it returns. The only minor gap is the lack of an output schema, but the description adequately describes the return value ('whether the formula is valid and what result type it produces'), making it sufficiently complete for agent use.

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?

With 100% schema description coverage, the input schema already fully documents all parameters. The description doesn't add any parameter-specific information beyond what's in the schema, so it meets the baseline of 3. It doesn't explain parameter relationships or provide additional semantic context about the formula validation process.

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 the specific action ('validate a formula expression'), the resource ('formula field'), and distinguishes it from siblings by explicitly mentioning its use 'before creating or updating a formula field' to catch errors early. It differentiates from tools like 'create_formula_field' and 'update_formula_field' by focusing on validation rather than creation/modification.

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 explicitly states when to use this tool: 'before creating or updating a formula field' to 'catch errors early.' It provides clear alternatives by naming the sibling tools 'create/update' that should follow validation, giving the agent specific guidance on workflow sequencing.

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