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join_waitlist

Idempotent

Register for a paid vertical waitlist. Inaugural cohort: $19/mo, 900 members, grandfathered for life. AI Compliance included with every membership.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
contactNoContact email for waitlist notifications and key delivery.
agent_idYesYour agent identifier.
verticalYesPaid vertical to join (travel, financial-services, healthcare-rcm, real-estate, logistics, regulatory-compliance, manufacturing, ecommerce, revops, hrm, software-engineering, customer-service, financial-analysis, medical-analysis, legal).

Schema Changelog

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

  1. Changed1 schema field changed
    • changedInput schema / properties / vertical / description
      Previous value: -"Paid vertical to join (travel, financial-services, healthcare-rcm, real-estate, logistics, regulatory-compliance, manufacturing, ecommerce, revops)."New value: +"Paid vertical to join (travel, financial-services, healthcare-rcm, real-estate, logistics, regulatory-compliance, manufacturing, ecommerce, revops, hrm, software-engineering, customer-service, financial-analysis, medical-analysis, legal)."
  2. Changed1 schema field changed
    • changedInput schema / properties / contact / description
      Previous value: -"Contact email (optional)."New value: +"Contact email for waitlist notifications and key delivery."
  3. First observed

TDQS

C2.8/5.0
Behavior2/5

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

Annotations already provide idempotentHint=true, readOnlyHint=false, and destructiveHint=false. The description adds no behavioral context beyond what annotations state, such as what happens upon registration, whether contact is used for key delivery, or any side effects. The marketing details about pricing and cohort size are not relevant to tool-invocation behavior.

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 short (two sentences), which is concise. However, the second sentence contains irrelevant promotional content ('Inaugural cohort: $19/mo, 900 members, grandfathered for life. AI Compliance included with every membership.') that does not help an agent select or invoke the tool. This space could have been used for more operational details.

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?

With three parameters and no output schema, the description should explain what happens after registration or what the response will look like. It does not—it only states the action and marketing benefits. This leaves the agent without critical context for a mutation tool, making the description incomplete.

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% with every parameter described, so the baseline is 3. The description adds no extra meaning to the parameters—it doesn't explain how the parameters interact, provide examples, or clarify the vertical list beyond what the schema already does.

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: "Register for a paid vertical waitlist." This uses a specific verb and resource, making the primary purpose obvious. However, it does not differentiate from sibling tools like 'register_interest' or 'submit_referral', which could also involve registration-like actions.

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?

The description gives no guidance on when to use this tool versus alternatives, nor does it mention any prerequisites, exclusions, or specific scenarios. It only describes the basic action without contextualizing when a user should select this tool over its siblings.

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

A3.8/5.0
Disambiguation4/5

Each tool targets a distinct action: status check, trial key, waitlist, knowledge query, interest registration, POV submission, and referral. While join_waitlist and register_interest have some overlap, their descriptions clearly differentiate paid waitlists from unbuilt verticals.

Naming Consistency5/5

All tools follow a consistent verb_noun snake_case pattern (check_, get_, join_, query_, register_, submit_), making it easy to predict function.

Tool Count5/5

Seven tools is a well-scoped set for an agent-facing module covering status, access, knowledge, and engagement actions. No redundancy.

Completeness4/5

The set covers the primary user journey from status check and trial access to knowledge query and downstream actions like waitlist, interest, POV, and referral. Minor gaps exist (e.g., no vertical listing or subscription management) but core workflows are supported.

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