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.
npx skills add Ad-Superpowers/ad-superpowers-plugin --skill google-ads-audience-strategy-plannergit clone --depth 1 https://github.com/Ad-Superpowers/ad-superpowers-pluginWrote 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.
[](https://agentmods.dev/skills/ad-superpowers/ad-superpowers-plugin/google-ads-audience-strategy-planner)<a href="https://agentmods.dev/skills/ad-superpowers/ad-superpowers-plugin/google-ads-audience-strategy-planner"><img src="https://agentmods.dev/badge/skills/ad-superpowers/ad-superpowers-plugin/google-ads-audience-strategy-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.
<a href="https://agentmods.dev/skills/ad-superpowers/ad-superpowers-plugin/google-ads-audience-strategy-planner"><img src="https://agentmods.dev/badge/skills/ad-superpowers/ad-superpowers-plugin/google-ads-audience-strategy-planner.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00107 | $0.01675 |
| Opus 5.5 | $0.00043 | $0.00670 |
| Sonnet 5.5 | $0.00021 | $0.00335 |
| Haiku 4.5 | $0.00011 | $0.00168 |
Grade A, and why
google-ads-audience-strategy-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.
How it starts
The opening of the file, as written. The whole thing — 160 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Audience Strategy Planner
Complete guide for setting up an effective Google Ads audience strategy with first-party data, Google audiences, and layering strategies for lead generation.
Quick decision guide for choosing audience strategy in references/decision-trees.md.
GAQL: Check Audience Performance
-- Audience observation data from Search campaigns
SELECT campaign.name, ad_group.name,
ad_group_criterion.user_list.user_list,
ad_group_criterion.bid_modifier,
metrics.impressions, metrics.clicks, metrics.cost_micros,
metrics.conversions, metrics.conversions_value
FROM ad_group_audience_view
WHERE segments.date DURING LAST_30_DAYS
AND campaign.advertising_channel_type = 'SEARCH'
ORDER BY metrics.impressions DESC
LIMIT 100
-- All Customer Match + remarketing lists
SELECT user_list.name, user_list.size_for_search,
user_list.size_for_display, user_list.membership_life_span,
user_list.type, user_list.eligible_for_search
FROM user_list
ORDER BY user_list.size_for_search DESC
LIMIT 50
Audience Types Overview
| Type | Description | Use Case |
|---|---|---|
| First-Party Data | ||
| Customer Match | Your customer lists (email, phone, address) | Upsell, loyalty, exclusion |
| Website Visitors | Remarketing lists (RLSA) | Re-engage, cart recovery |
| YouTube Users | Video interactions | Video remarketing |
| GA4 Audiences | Behavioral segments | Complex targeting |
| Google-Provided | ||
| In-market | Actively researching products | High-intent prospecting |
| Affinity | Long-term interests & lifestyle | Brand awareness |
| Life Events | Major life changes (moving, wedding) | Timely targeting |
| Detailed Demographics | Age, gender, income, parental | Demographic targeting |
| Optimized Targeting | Google expands beyond selections | Scale acquisition |
| Custom Segments | Keywords, URLs, app interests | Custom intent targeting |
Optimized Targeting replaced Similar Audiences (deprecated May 2023). Enabled by default in Display, YouTube, and Demand Gen.
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.
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.
- 1mo ago First seen · 160 lines · 107 tokens per session scan A 29637696925f
google-ads-audience-strategy-planner is a skill published in the GitHub repository Ad-Superpowers/ad-superpowers-plugin (5 stars, last pushed 29d ago), licensed MIT. It adds 107 tokens to every session and 1,675 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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