contact_field_listRetrieve custom contact field keys, names, and types for an organization so you can map them when creating or updating contacts.
List the custom contact fields defined in an organization (key, name, type: 0 = text, 1 = link, 2 = button). Use the keys with contact_create and contact_update.
| Name | Required | Description | Default |
|---|---|---|---|
| organizationId | Yes | The organization id. Use organization_list to find it. |
Changes observed during successful MCP inspections.
v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is fully carried by structured data. The description adds the type-code legend (0=text, 1=link, 2=button), which is genuinely useful return-value context not present anywhere in the schema, but it says nothing about pagination, ordering, or filtering behavior.
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?
Two sentences with zero filler, front-loaded with purpose, then returning the type legend and downstream usage. Every clause earns its place.
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 simple read-only list tool, the definition covers purpose, key return fields, the type-code mapping, and the follow-up workflow, while annotations cover safety and the schema covers the single required argument. Nothing an agent needs to invoke it correctly is missing.
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 single organizationId parameter is fully described in the schema (100% coverage), including a pointer to organization_list. The description adds no additional parameter meaning, so the schema-does-the-work baseline of 3 applies.
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?
States a specific verb (List), resource (custom contact fields), and scope (defined in an organization), and even enumerates the returned attributes (key, name, type). An agent can distinguish this from contact_list, contact_create, and contact_update without opening a 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?
Explicitly names the downstream consumers: 'Use the keys with contact_create and contact_update.' This tells the agent why it would call the tool and what to do with the result, though there are no exclusions or when-not conditions (which are arguably unnecessary for a discovery endpoint).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.