google-ads-demand-gen-planner

google-ads-demand-gen-planner is a skill for Claude Code from Ad-Superpowers/ad-superpowers-plugin. It costs 109 tokens per session (6,208 once invoked), scanned A, original, MIT.

A guide for planning Demand Gen campaigns, Google’s visual advertising campaigns across YouTube, Discover, Gmail, and YouTube Shorts. It covers image, video, carousel, and product-feed ads for reaching people before they are ready to buy.

In plain words
What is it for?
Use it to plan Demand Gen campaigns, migrate from Discovery, configure Gmail or YouTube Shorts advertising, and choose visual ad formats.
Why use it?
It explains how Demand Gen differs from the older Discovery campaign type and helps turn a visual advertising goal into a suitable campaign plan.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the ad-superpowers plugin — 120 skills, 35 commands, 5 agents, 1 MCP server shipped together

Good fit Use it to plan Demand Gen campaigns, migrate from Discovery, configure Gmail or YouTube Shorts advertising, and choose visual ad formats.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/ad-superpowers/ad-superpowers-plugin/google-ads-demand-gen-planner
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add Ad-Superpowers/ad-superpowers-plugin --skill google-ads-demand-gen-planner
Clone the repo
git clone --depth 1 https://github.com/Ad-Superpowers/ad-superpowers-plugin

Made for: Claude Code.

Or install ad-superpowers, the plugin that ships this one along with the rest of its 120 skills, 35 commands, 5 agents, 1 MCP server.

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 google-ads-demand-gen-planner

README.md
[![agentmods](https://agentmods.dev/badge/skills/ad-superpowers/ad-superpowers-plugin/google-ads-demand-gen-planner/github.svg)](https://agentmods.dev/skills/ad-superpowers/ad-superpowers-plugin/google-ads-demand-gen-planner)
Your own site
<a href="https://agentmods.dev/skills/ad-superpowers/ad-superpowers-plugin/google-ads-demand-gen-planner"><img src="https://agentmods.dev/badge/skills/ad-superpowers/ad-superpowers-plugin/google-ads-demand-gen-planner/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 google-ads-demand-gen-planner

Your own site · 80×15
<a href="https://agentmods.dev/skills/ad-superpowers/ad-superpowers-plugin/google-ads-demand-gen-planner"><img src="https://agentmods.dev/badge/skills/ad-superpowers/ad-superpowers-plugin/google-ads-demand-gen-planner.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 109 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 6,208 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 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 $0.00109 $0.06208
Opus 5.5 $0.00044 $0.02483
Sonnet 5.5 $0.00022 $0.01242
Haiku 4.5 $0.00011 $0.00621

Measured 1mo ago against content hash 5f90fd9cba63, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

google-ads-demand-gen-planner scanned grade A with 0 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 1mo ago.

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.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

plugin/skills/google-ads-demand-gen-planner/SKILL.md · 787 lines

How it starts

The opening of the file, as written. The whole thing — 787 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Demand Gen Planner

Complete guide to Google Ads Demand Gen campaigns — the successor to Discovery campaigns for visual, mid-funnel advertising on YouTube, Discover, Gmail, and YouTube Shorts.

See decision-trees.md for details.

What is Demand Gen?

From Discovery to Demand Gen

DEMAND GEN EVOLUTION
════════════════════

DISCOVERY ADS (2019-2023)     →     DEMAND GEN (2024+, incl. Video Action 2025)
────────────────────────────────────────────────────────────────────────────────

Placements:                    Placements (expanded):
├── YouTube Home               ├── YouTube Home
├── Discover Feed              ├── YouTube Watch Next
├── Gmail Promotions           ├── YouTube Shorts ⭐ (added 2024)
└── Gmail Social               ├── Discover Feed
                               ├── Gmail Promotions
Formats:                       └── Gmail Social
├── Single image
├── Carousel                   Formats (expanded):
└── Product feeds              ├── Single image
                               ├── Carousel
Bidding:                       ├── Video ads (incl. former Video Action)
├── tCPA                       ├── Product feeds
└── Maximize conversions       └── Mixed (image + video)

                               Bidding (expanded):
                               ├── tCPA
                               ├── Maximize conversions
                               ├── tROAS (added v22)
                               ├── Maximize clicks
                               └── Maximize conversion value

                               Features (2024-2025):
                               ├── Lookalike segments
                               ├── A/B creative experiments
                               ├── Video Action format absorbed
                               └── Enhanced audience tools

NOTE: Video Action Campaigns were merged into Demand Gen in 2025.
      If you need conversion-optimized video ads, use Demand Gen with
      tCPA/Maximize Conversions and video assets — not a separate VAC.
      Discovery campaigns were sunset in 2023/2024.

Read the full file on GitHub · 787 lines

Files

What ships with it

2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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. 1mo ago First seen · 787 lines · 109 tokens per session scan A 5f90fd9cba63

Subscribe to this mod's changes

google-ads-demand-gen-planner is a skill published in the GitHub repository Ad-Superpowers/ad-superpowers-plugin (5 stars, last pushed 1mo ago), licensed MIT. It adds 109 tokens to every session and 6,208 once invoked, about $0.0004 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-11.

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