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.
git clone --depth 1 https://github.com/thatrebeccarae/claude-marketingWrote 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/rules/thatrebeccarae/claude-marketing/facebook-ads)<a href="https://agentmods.dev/rules/thatrebeccarae/claude-marketing/facebook-ads"><img src="https://agentmods.dev/badge/rules/thatrebeccarae/claude-marketing/facebook-ads/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/rules/thatrebeccarae/claude-marketing/facebook-ads"><img src="https://agentmods.dev/badge/rules/thatrebeccarae/claude-marketing/facebook-ads.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 | $0.00055 | $0.01856 |
| Opus 5 | $0.00028 | $0.00928 |
| Sonnet 5 | $0.00011 | $0.00371 |
| Haiku 4.5 | $0.00006 | $0.00186 |
Grade A, and why
facebook-ads 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 9d 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 — 146 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Meta Ads (Facebook & Instagram)
Expert-level guidance for Meta Ads — auditing, building, and optimizing campaigns across Facebook, Instagram, Messenger, and the Audience Network.
Core Capabilities
Campaign Auditing & Optimization
- Full account audit: structure, objectives, audiences, creative, tracking, attribution
- Identify creative fatigue, audience overlap, and budget inefficiencies
- Diagnose performance drops (iOS privacy, audience saturation, creative burnout)
- Advantage+ Shopping and Advantage+ Audience recommendations
Campaign Objectives (Outcome-Based)
- Awareness — Reach, brand awareness, video views
- Traffic — Link clicks, landing page views
- Engagement — Post engagement, messages, conversions on-platform
- Leads — Instant Forms, Messenger, website lead gen
- App Promotion — App installs, app events
- Sales — Website conversions, catalog sales, Advantage+ Shopping
Audience Strategy
- Core Audiences — Demographics, interests, behaviors, location
- Custom Audiences — Website (pixel/CAPI), customer list, app activity, video viewers, engagement
- Lookalike Audiences — 1-10% based on custom audience seed (value-based LALs preferred)
- Advantage+ Audience — Meta's AI-driven targeting (audience suggestions as signals, not constraints)
- Broad targeting — No interests/LAL, rely on creative + pixel data + Meta's ML
Creative Strategy
- Ad format selection: single image, carousel, video, collection, Instant Experience
- Creative testing frameworks: concept testing vs iterative testing
- UGC (user-generated content) integration and creator whitelisting
- Dynamic Creative Optimization (DCO) vs manual A/B testing
- Creative fatigue signals and refresh cadence
- Platform-specific creative (Feed, Stories, Reels, Explore)
Tracking & Attribution
- Meta Pixel — Standard events, custom events, microdata, aggregated event measurement
- Conversions API (CAPI) — Server-side tracking for privacy resilience
- Aggregated Event Measurement (AEM) — iOS 14.5+ handling, 8-event prioritization
- Attribution settings: 7-day click + 1-day view (default), 1-day click, 28-day click
- UTM parameter strategy for GA4 cross-reference
- Conversion lift studies and incrementality testing
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.
- 9d ago First seen · 146 lines · 55 tokens per session scan A 8f606bd382e2
facebook-ads is a cursor rule published in the GitHub repository thatrebeccarae/claude-marketing (133 stars, last pushed 3mo ago), licensed MIT. It adds 55 tokens to every session and 1,856 once invoked, about $0.0003 per session on Opus 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 2026-08-30.
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