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List custom fields

lacrm_list_custom_fields
Read-only

List the account's field definitions (name, type, options) for contacts, companies or pipelines — use the Name values as keys in custom_fields when creating/editing contacts. LACRM: GetCustomFields.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pageNoPage number, 1-based. Default 1.
max_resultsNoResults per page (MaxNumberOfResults), 1-10000. Default here: 50.
pipeline_idNoFor pipeline fields, only this pipeline's (a long numeric Uid — always pass it as a string).
record_typeNoOnly fields for this record type.
include_archivedNoInclude deleted fields. Default false.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / $schema
      Previous value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"
  2. First observed

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, so the safety profile is covered. The description adds real behavioral value by disclosing the cross-tool contract (returned Name values are the keys accepted in custom_fields), which no annotation or schema conveys.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

A single dense sentence that front-loads the action and purpose, then the practical usage note, followed by a compact API-name tag. No filler or redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema, the description steps in by naming the returned attributes (name, type, options) and the three record types. It is callable as-is; only pagination/return-envelope behavior is left implicit, which is minor for a read-only metadata listing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents page, max_results, pipeline_id, record_type, and include_archived. The description adds only the 'name, type, options' output hint and the record_type enumeration in prose, so it neither compensates nor detracts — baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ('List the account's field definitions') and enumerates what is returned (name, type, options) plus the record-type scope. This clearly distinguishes it from sibling list tools that return records (contacts, pipelines, tasks) rather than field metadata.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives a concrete when-to-use: 'use the Name values as keys in custom_fields when creating/editing contacts,' tying it to lacrm_create_contact/lacrm_edit_contact. No explicit when-not or alternative tool is named, but the context is unambiguous for a metadata-lookup tool.

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

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