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 meta-audience-overlap-detectorgit 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/meta-audience-overlap-detector)<a href="https://agentmods.dev/skills/ad-superpowers/ad-superpowers-plugin/meta-audience-overlap-detector"><img src="https://agentmods.dev/badge/skills/ad-superpowers/ad-superpowers-plugin/meta-audience-overlap-detector/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/meta-audience-overlap-detector"><img src="https://agentmods.dev/badge/skills/ad-superpowers/ad-superpowers-plugin/meta-audience-overlap-detector.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 | $0.00095 | $0.02731 |
| Opus 5.5 | $0.00038 | $0.01092 |
| Sonnet 5.5 | $0.00019 | $0.00546 |
| Haiku 4.5 | $0.00010 | $0.00273 |
Grade A, and why
meta-audience-overlap-detector 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 — 322 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Audience Overlap Detector
Overview
This skill helps identify audience overlap in Meta Ads accounts, which leads to internal competition (self-bidding), higher costs, and inconsistent delivery. It provides frameworks for overlap analysis and solution strategies.
Why Overlap Is Problematic
┌─────────────────────────────────────────────────────────────────┐
│ AUCTION DYNAMICS WITH OVERLAP │
│ │
│ User "Anna" is in: │
│ ├── Ad Set A: Interest "Fitness" │
│ ├── Ad Set B: Lookalike 1% Purchasers │
│ └── Ad Set C: Website Visitors 30d │
│ │
│ Result: │
│ ├── You bid 3x against yourself for the same impression │
│ ├── CPM rises artificially │
│ ├── Budget is distributed inefficiently │
│ └── Learning phase takes longer (split data) │
└─────────────────────────────────────────────────────────────────┘
Overlap Check Method
Step 1: Audience Overlap Tool (Meta)
Location: Ads Manager → Audiences → Select 2+ audiences →
Actions → Show Audience Overlap
Interpretation:
├── <10% overlap: Acceptable, no action needed
├── 10-30% overlap: Monitor, consider exclusions
├── 30-50% overlap: Problematic, consolidate or exclude
└── >50% overlap: Critical, merge audiences
Step 2: Create Overlap Matrix
Ask the user to share their audiences, and create a matrix:
AUDIENCE OVERLAP MATRIX
=======================
│ Broad │ LAL 1% │ LAL 3% │ Interest │ Retarg │
──────────────┼───────┼────────┼────────┼──────────┼────────┤
Broad │ - │ 15% │ 25% │ 35% │ 5% │
LAL 1% │ 15% │ - │ 70% │ 20% │ 10% │
LAL 3% │ 25% │ 70% │ - │ 30% │ 15% │
Interest │ 35% │ 20% │ 30% │ - │ 8% │
Retargeting │ 5% │ 10% │ 15% │ 8% │ - │
Critical: LAL 1% <> LAL 3% = 70% overlap
Warning: Broad <> Interest = 35% overlap
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 · 322 lines · 95 tokens per session scan A aea61d24ed67
meta-audience-overlap-detector is a skill published in the GitHub repository Ad-Superpowers/ad-superpowers-plugin (5 stars, last pushed 29d ago), licensed MIT. It adds 95 tokens to every session and 2,731 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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