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TylerIlunga

Procore MCP Server

get_all_custom_fields

Retrieve all custom fields for a company from Procore's workforce planning system. Use this tool to access and manage custom field configurations through the Procore MCP Server.

Instructions

Get All Custom Fields. [Company Admin/Custom - Configurable Tools] GET /rest/v1.0/workforce-planning/v2/companies/{company_id}/custom-fields

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
company_idYesUnique identifier for the company. This parameter accepts both formats: - **Recommended**: Procore company ID (integer) - Use this for new integrations - Legacy: LaborChart UUID format (uuid string...
pageNoPage number for pagination
per_pageNoItems per page (max 100)
Behavior2/5

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

No annotations are provided, so the description carries the full burden. It states 'GET' (implying read-only) and mentions pagination parameters in the schema, but doesn't explicitly disclose that it's a safe read operation, potential rate limits, authentication needs, or what 'All' entails (e.g., scope across projects). The bracketed '[Company Admin/Custom - Configurable Tools]' hints at permissions but isn't clear.

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

Conciseness3/5

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

The description is brief but includes extraneous technical details (API path) that don't aid an AI agent. It's front-loaded with the core purpose but wastes space on implementation specifics. The bracketed text adds minor context but could be integrated more cleanly.

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

Completeness2/5

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

Given no annotations and no output schema, the description is incomplete. It doesn't explain the return format (e.g., list of custom field objects), pagination behavior, or error cases. For a list operation with 3 parameters, this leaves significant gaps for an agent to infer behavior.

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%, with clear docs for company_id (including format details), page, and per_page. The description adds no parameter semantics beyond what's in the schema. With high schema coverage, the baseline is 3, as the description doesn't compensate but also doesn't detract.

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

Purpose2/5

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

The description 'Get All Custom Fields' is a tautology that restates the tool name without adding specificity. It mentions the resource ('Custom Fields') but lacks a clear verb beyond 'Get' and doesn't distinguish from sibling tools (e.g., 'get_single_custom_field'). The bracketed text '[Company Admin/Custom - Configurable Tools]' and API path provide technical context but don't clarify the tool's purpose for an AI agent.

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

Usage Guidelines2/5

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

No guidance is provided on when to use this tool versus alternatives. The description doesn't mention sibling tools like 'get_single_custom_field' or 'list_custom_field_definitions', nor does it specify prerequisites (e.g., company admin permissions implied by bracketed text). The agent must infer usage from the name alone.

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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