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

With annotations already covering readOnly=false, openWorld=false, idempotent=true, and destructive=false, the description still adds important behavioral context: admin and plan prerequisites, partial-failure behavior where the object and fields are not undone together, the fact that a failed call cannot be retried for the same object, and that the tool calls no outside service. It also explains the exact semantics of retrying with the same idempotencyKey. These are meaningful disclosures beyond the structured annotations.

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, then layers prerequisites, failure behavior, consent requirements, and safety notes. For a complex, high-risk mutation, most sentences earn their place, though the consent guardrails are somewhat repetitive and could be tightened. It remains readable and well organized despite its length.

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?

There is no output schema, annotations cover only basic safety and idempotency, and schema description coverage is very low, yet the description provides the missing context an agent needs: admin-only access, plan requirement, naming conventions, field-type constraints, partial-failure handling, consent protocol, and downstream visibility in list_objects. It is complete enough for correct invocation given the tool's complexity and the remaining structured-field gaps.

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 only 10% for 10 parameters, so the description must carry most of the semantic burden. It adds useful meaning for nameSingular, namePlural, labelSingular, and labelPlural, and it clarifies that SELECT/MULTI_SELECT fields need options and CURRENCY fields need a currencyCode. However, it leaves several parameters unexplained—including confirm, icon, workspaceId, and most field-level attributes—so it only partially compensates for the schema gap.

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 states a specific verb (creates), resource (one new custom object type and its fields), and scope (a record type the workspace does not have yet), with concrete examples like invoice or contract. It distinguishes itself from siblings by naming list_objects and create_record as downstream tools and by excluding relation and raw-JSON fields, which belong in workspace settings. An agent can tell this apart from create_custom_field and similar tools without opening the 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?

It explicitly states the prerequisite conditions: only a workspace admin may call it, the workspace plan must include custom objects, and relation or raw-JSON fields must be added elsewhere. It gives strong when-to-call and when-not-to-call guidance, including a mandatory consent protocol requiring explicit user go-ahead in the same turn, and it routes partial failures to workspace settings instead of retries. Alternatives and post-conditions are named, so there is little left to infer.

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