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clerk.create_waitlist_entries

Add one or more email addresses to the waitlist in a connected Clerk application.

Call clerk.get_connected_accounts first. Pass clerk_instance_id to target a specific connection, or omit it to use the default account.

Returns the created or existing waitlist entries.

Cost = 10 tokens.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
waitlist_entriesYesOne or more waitlist entry objects. Each item requires email_address (string). Optional fields per item: notify (boolean; whether to notify the user their email was added; defaults to true).
clerk_instance_idNoClerk instance id (ins_...) from clerk.get_connected_accounts. Omit to use the default connected account.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
waitlist_entriesNoCreated or existing Clerk waitlist entry summaries.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Added

TDQS

A4.2/5.0
Behavior4/5

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

With no annotations provided, the description carries the burden. It discloses the return behavior ('Returns the created or existing waitlist entries'), a prerequisite call, and a cost token amount. It does not mention side effects beyond adding, but for a simple creation tool this is reasonable. It also implies idempotency by returning existing entries.

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?

The description is four sentences, with the main action front-loaded and no padding. Each sentence earns its place: purpose, prerequisite/instance selection, return value, and cost. It is concise and well-structured.

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?

Given the low complexity (2 params, full schema descriptions, output schema present), the description covers all critical information: what it does, prerequisite, how to target an instance, return value, and cost. It lacks explicit alternatives but that is not essential for completeness here.

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 coverage is 100% and both parameters have detailed descriptions. The tool description only echoes the schema's guidance for clerk_instance_id and provides no new meaning for waitlist_entries beyond what the schema already states. Therefore, it adds no value beyond the baseline.

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?

The description opens with a specific verb and resource: 'Add one or more email addresses to the waitlist in a connected Clerk application.' This clearly distinguishes the tool from sibling tools like list_waitlist_entries, invite_waitlist_entry, reject_waitlist_entry, and delete_waitlist_entry by focusing on creation/addition.

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?

It provides explicit usage guidance: 'Call clerk.get_connected_accounts first' and 'Pass clerk_instance_id to target a specific connection, or omit it to use the default account.' This gives clear context on prerequisites and parameter selection, though it does not explicitly name alternatives or when-not-to-use cases.

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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TDQS

A4.1/5.0
Disambiguation5/5

Each tool has a distinct purpose, further clarified by group prefixes and clear descriptions. Within each group, tools perform different operations (e.g., domains.lookup vs. domains.whois vs. domains.rdap) with no ambiguity.

Naming Consistency5/5

All tools follow a consistent group.tool_name pattern using snake_case. The naming is predictable and uniformly applied across all groups.

Tool Count4/5

78 tools is high, but the server aggregates multiple distinct API domains (11 groups). Each group has a reasonable number of tools, typically under 10, with TikTok having 17. The count reflects breadth, not bloat.

Completeness5/5

Each domain's tool set covers the primary expected operations (e.g., search, details, reviews, metrics, user info). There are no obvious gaps for read-only analytical use; features like posting are likely out of scope.