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 itallstartedwithaidea/agent-skills --skill remarketing-strategygit clone --depth 1 https://github.com/itallstartedwithaidea/agent-skillsWrote 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/itallstartedwithaidea/agent-skills/remarketing-strategy)<a href="https://agentmods.dev/skills/itallstartedwithaidea/agent-skills/remarketing-strategy"><img src="https://agentmods.dev/badge/skills/itallstartedwithaidea/agent-skills/remarketing-strategy/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/itallstartedwithaidea/agent-skills/remarketing-strategy"><img src="https://agentmods.dev/badge/skills/itallstartedwithaidea/agent-skills/remarketing-strategy.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 | $0.00031 | $0.03076 |
| Opus 5.5 | $0.00012 | $0.01230 |
| Sonnet 5.5 | $0.00006 | $0.00615 |
| Haiku 4.5 | $0.00003 | $0.00308 |
Grade A, and why
remarketing-strategy 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 — 303 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Remarketing Strategy
Part of Agent Skills™ by googleadsagent.ai™
Description
The Remarketing Strategy skill designs and implements cross-channel remarketing architectures that re-engage users at every stage of the conversion funnel. Remarketing is consistently the highest-ROI tactic in digital advertising because it targets users who have already demonstrated interest. This skill transforms basic "show ads to past visitors" approaches into sophisticated, funnel-aware remarketing systems with sequential messaging, frequency controls, and cross-device orchestration.
The skill segments audiences by funnel position and engagement depth: top-of-funnel visitors (single-page sessions), mid-funnel engagers (multi-page sessions, content consumers), bottom-of-funnel prospects (cart abandoners, form starters, pricing page viewers), and post-conversion customers (for upsell and retention). Each segment receives tailored messaging that matches their relationship with the brand, from awareness reinforcement to urgency-driven conversion nudges.
Cross-channel execution spans Display remarketing, YouTube remarketing, RLSA (Remarketing Lists for Search Ads), dynamic remarketing with product-specific creative, and customer journey mapping across devices. The skill implements frequency capping to prevent ad fatigue, membership duration optimization to balance reach and relevance, and sequential messaging chains that progressively move users toward conversion. It also manages negative audience layering to prevent redundant messaging and wasted impressions.
Use When
- User asks about "remarketing" or "retargeting" strategy
- User mentions "remarketing lists" or "audience segmentation"
- User wants to "re-engage" past visitors or abandoned carts
- User asks about "frequency capping" or "ad fatigue"
- User mentions "RLSA" or "remarketing for search"
- User asks about "dynamic remarketing" or "product remarketing"
- User wants to build a "customer journey" or "sequential messaging"
- User mentions "cross-device" targeting or "cross-channel" remarketing
- User asks about "membership duration" or "audience window" optimization
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 · 303 lines · 31 tokens per session scan A 050a0c887130
remarketing-strategy is a skill published in the GitHub repository itallstartedwithaidea/agent-skills (44 stars, last pushed 6mo ago), licensed MIT. It adds 31 tokens to every session and 3,076 once invoked, about $0.0001 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 2026-08-30.
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