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AIWerk

@aiwerk/mcp-server-ghl

by AIWerk

ad_manager_fb_create_page_lead_form

Create a Facebook page lead form by specifying the page, questions, privacy policy, and thank-you page to capture leads directly from ads.

Instructions

Create page lead form

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesLead form name
typeYesLead form type
pageIdYesFacebook page identifier
questionsYesList of questions displayed on the lead form
locationIdNoLocation identifier Defaults to GHL_LOCATION_ID when omitted.
greetingCardNoGreeting card config
thankYouPageYesThank you page config
customDisclaimerNoCustom disclaimer config
privacyPolicyLinkYesPrivacy policy URL
privacyPolicyTextNoPrivacy policy text
questionPageHeadlineNoQuestion page headline
Behavior2/5

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

Annotations indicate readOnlyHint=false (a write operation) and destructiveHint=false (not destructive). The description confirms the action but adds no new behavioral detail beyond what the annotations already convey. It doesn't disclose any side effects, auth requirements, or rate limits. Since the annotations already signal mutation, the description adds minimal value here.

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

Conciseness2/5

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

The description is a single short phrase, which is concise but extremely under-specified for a tool with 11 parameters and nested objects. It does front-load the main action but fails to provide any supporting structure or context. This is under-specification rather than effective conciseness.

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?

The tool is complex (nested objects, 6 required fields) but the description offers no high-level context about how to use it, what the typical workflow is, or any constraints. The schema provides parameter details, but the overall context—such as the need for a Facebook page ID and integration setup—is entirely absent. The description is inadequate for an agent to confidently invoke this tool.

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?

The input schema provides descriptions for all 11 parameters, so schema coverage is 100%. The description does not add any parameter-specific semantics beyond what the schema already documents. Given this high coverage, the baseline score of 3 applies—the description doesn't enhance or clarify parameter usage.

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

Purpose4/5

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

The description clearly states the action 'Create page lead form' with a specific verb and resource. However, it does not distinguish this from sibling tools like ad_manager_fb_create_conversation_form, which also creates a Facebook form type. Without additional context, an agent might confuse it with similar tools, but the core purpose is unambiguous.

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

Usage Guidelines1/5

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

There is no guidance on when to use this tool versus alternatives, no prerequisites (e.g., having a Facebook page already integrated), and no mention of typical scenarios. The description simply states the action without any usage context, leaving the agent to infer everything from the schema.

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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