Add custom fields to company records in HubSpot CRM to track specific business data, enabling tailored data collection and organization for improved customer relationship management.
Create a new company property
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | ||
| label | Yes | ||
| type | Yes | ||
| fieldType | Yes | ||
| groupName | Yes | ||
| description | No | ||
| options | No | ||
| displayOrder | No | ||
| hasUniqueValue | No | ||
| hidden | No | ||
| formField | No |
Changes observed during successful MCP inspections.
v1.0.0Input schema / $schemaAdded value: +"http://json-schema.org/draft-07/schema#"Input schema / additionalPropertiesAdded value: +falseDoes the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states 'Create a new company property' but does not clarify whether this is a mutating operation, what permissions are needed, if there are rate limits, or what happens on success/failure. For a creation tool with 11 parameters and no annotation coverage, this is a significant gap in transparency.
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 extremely concise—a single sentence with no wasted words. It is front-loaded and directly states the tool's action. While this brevity contributes to clarity in structure, it comes at the cost of informational completeness.
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 (11 parameters, 5 required, 2 enums), lack of annotations, and no output schema, the description is severely incomplete. It does not explain the tool's behavior, parameter meanings, or expected outcomes. For a creation tool in a CRM context, this leaves critical gaps for an AI agent to understand and use the tool correctly.
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 description coverage is 0%, meaning none of the 11 parameters have descriptions in the schema. The tool description adds no information about parameters, such as what 'fieldType', 'type', or 'options' mean in context. With 5 required parameters and complex enums, the description fails to compensate for the lack of schema documentation.
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 'Create a new company property' restates the tool name with minimal elaboration. While it specifies the verb ('create') and resource ('company property'), it lacks detail on what a 'company property' entails or how it differs from sibling tools like crm_create_contact_property or crm_create_lead_property. This is closer to a tautology than a clear, distinct purpose statement.
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 no guidance on when to use this tool versus alternatives. It does not mention prerequisites (e.g., required permissions), context for creating company properties, or how it relates to sibling tools such as crm_get_company_properties or crm_update_company. Without any usage context, the agent must infer everything from the tool name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.