awesome-workplaces-skills: Skill for Codex

.agents/skills/gmail-waitlist/SKILL.md

gmail-waitlist is a skill for Codex from moose-lab/awesome-workplaces-skills. It costs 62 tokens per session (2,820 once invoked), scanned B, original, MIT.

A signup form that collects email addresses and sends each signup to a Gmail inbox as a notification. It uses Google Cloud, Vercel serverless hosting, and the Gmail API, with no separate database.

In plain words
What is it for?
Use it for early-access lists, product waitlists, email capture on landing pages, and signup notifications managed through Gmail.
Why use it?
It removes the need to run a database or pay for a separate email service for a typical waitlist.

Skill for Codex

Written for Codex: agents/openai.yaml present. Also seen: positional $N argument; installed under .agents/ (shared by several agents).

This is moose-lab/awesome-workplaces-skills's own configuration. It tells Codex how to work on awesome-workplaces-skills itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything awesome-workplaces-skills configures →

Reuse

Borrowing it

Nothing to install: this file belongs to moose-lab/awesome-workplaces-skills. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/moose-lab/awesome-workplaces-skills/main/.agents/skills/gmail-waitlist/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/moose-lab/awesome-workplaces-skills

Made for: Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for gmail-waitlist

README.md
[![agentmods](https://agentmods.dev/badge/skills/moose-lab/awesome-workplaces-skills/gmail-waitlist/github.svg)](https://agentmods.dev/skills/moose-lab/awesome-workplaces-skills/gmail-waitlist)
Your own site
<a href="https://agentmods.dev/skills/moose-lab/awesome-workplaces-skills/gmail-waitlist"><img src="https://agentmods.dev/badge/skills/moose-lab/awesome-workplaces-skills/gmail-waitlist/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for gmail-waitlist

Your own site · 80×15
<a href="https://agentmods.dev/skills/moose-lab/awesome-workplaces-skills/gmail-waitlist"><img src="https://agentmods.dev/badge/skills/moose-lab/awesome-workplaces-skills/gmail-waitlist.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 62 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,820 The whole file, excluding the scripts and references it only reads on demand.
Security scan B 2 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00062 $0.02820
Opus 5 $0.00031 $0.01410
Sonnet 5 $0.00012 $0.00564
Haiku 4.5 $0.00006 $0.00282

Measured 12d ago against content hash edd37ecacec6, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade B, and why

gmail-waitlist scanned grade B with 2 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.

The scan reads SKILL.md. This mod also ships 4 executable files (examples/form-handler.js, examples/server.js, examples/waitlist.js, …), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Sends data to an external URLmediumData exfiltration

A POST to an outside endpoint may be telemetry or may be exfiltration; either way the mod talks to somewhere, and you should know where.

Run `node server.js` and in another terminal: `curl -X POST http://localhost:3000/api/waitlist -H "Content-Type: application/json" -d '{"email":"[email protected]"}'` — expect `{"success":true}`. If `ECONNREFUSED`, the se

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

Run `node server.js` and in another terminal: `curl -X POST http://localhost:3000/api/waitlist -H "Content-Type: application/json" -d '{"email":"[email protected]"}'` — expect `{"success":true}`. If `ECONNREFUSED`, the se
.agents/skills/gmail-waitlist/SKILL.md · 261 lines

How it starts

The opening of the file, as written. The whole thing — 261 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Gmail Waitlist

Overview

Build a complete email waitlist that sends a Gmail notification whenever someone signs up. The entire stack runs at zero cost using GCP OAuth, a Vercel serverless function, and the Gmail API. No database required — every signup arrives as an email in your inbox.

What you get:

  • api/waitlist.js — Vercel serverless function (receives email, sends you a Gmail notification)
  • Frontend form handler — async submit with loading/error/success states
  • Gmail as the "database" — search, label, and export signups using Gmail's built-in tools

Total cost: $0/month for typical waitlist volumes (Vercel free tier + Gmail API free tier).

Prerequisites

Verify these are installed before proceeding:

  • Google account with Gmail
  • Node.js 18+ (node --version)
  • gcloud CLI (gcloud --version; install with brew install google-cloud-sdk on macOS)
  • Vercel CLI (vercel --version; install with npm i -g vercel)
  • gws CLI (npx @googleworkspace/cli --version; install with npm i -g @googleworkspace/cli)

Phase 1: GCP Project Setup

Create a Google Cloud project, enable the Gmail API, and configure OAuth credentials.

Inputs: Google account, desired GCP project ID Outputs: GMAIL_CLIENT_ID, GMAIL_CLIENT_SECRET → save for Phase 2

Detailed walkthrough: See references/gcp-setup.md

Steps

  1. Create a GCP project and enable the Gmail API:

    gcloud projects create YOUR_PROJECT_ID --name="Your Project Name"
    gcloud config set project YOUR_PROJECT_ID
    gcloud services enable gmail.googleapis.com
    
  2. Configure the OAuth consent screen at the Google Cloud Console:

    • Select External user type
    • Fill in the app name, user support email, and developer email
    • Add the scope https://www.googleapis.com/auth/gmail.send
    • Add your Gmail address as a test user
  3. Create OAuth client credentials:

    • Navigate to CredentialsCreate CredentialsOAuth client ID
    • CRITICAL: Select "Desktop app" as the application type
    • Name it (e.g., "Waitlist CLI")
    • Copy the Client ID and Client Secret

Read the full file on GitHub · 261 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 12d ago First seen · 261 lines · 62 tokens per session scan B edd37ecacec6

Subscribe to this mod's changes

gmail-waitlist is a skill published in the GitHub repository moose-lab/awesome-workplaces-skills (2 stars, last pushed 5mo ago), licensed MIT. It adds 62 tokens to every session and 2,820 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it B with 2 findings (sends data to an external url, makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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