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 Infinite-Labs-AI/infinite-skills --skill paid-adsgit clone --depth 1 https://github.com/Infinite-Labs-AI/infinite-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/infinite-labs-ai/infinite-skills/paid-ads)<a href="https://agentmods.dev/skills/infinite-labs-ai/infinite-skills/paid-ads"><img src="https://agentmods.dev/badge/skills/infinite-labs-ai/infinite-skills/paid-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/skills/infinite-labs-ai/infinite-skills/paid-ads"><img src="https://agentmods.dev/badge/skills/infinite-labs-ai/infinite-skills/paid-ads.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00038 | $0.00478 |
| Opus 5.5 | $0.00015 | $0.00191 |
| Sonnet 5.5 | $0.00008 | $0.00096 |
| Haiku 4.5 | $0.00004 | $0.00048 |
Grade A, and why
paid-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 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.
What it actually says
Paid Ads
Review paid acquisition to decide what to cut, fix, test, or scale.
Required Context
Use available platform exports, screenshots, campaign structure, UTMs, landing pages, CRM data, or spend summaries. If data is missing, ask for:
- Channel and objective.
- Spend, conversions, revenue, CAC, CPA, ROAS, or pipeline.
- Attribution window and conversion definition.
- Audience and offer.
- Creative examples.
- Landing page.
- Budget and time period.
Do not infer performance from structure alone when spend and conversion data exist.
Diagnose The System
Inspect:
- Economics: target CAC/CPA, payback, LTV, gross margin, sales cycle.
- Signal: conversion tracking quality and event meaning.
- Structure: campaign objective, segmentation, budget allocation, bidding logic.
- Audience: targeting, exclusions, intent, saturation.
- Creative: message variety, proof, format fit, fatigue.
- Landing path: match between ad promise and page.
- Learning: what tests have been run and what changed.
Give the data a confidence grade before recommending budget moves. Weak tracking should produce repair or learn recommendations, not scale recommendations.
Classify Issues
- Tracking issue: data cannot support decisions.
- Offer issue: click interest does not convert.
- Message issue: creative attracts wrong or weak intent.
- Audience issue: targeting is too broad, too narrow, or stale.
- Economics issue: campaign works mechanically but cannot pay back.
- Scale issue: winner exists but budget, creative, or funnel cannot absorb more.
Output
Paid acquisition read:
[one paragraph]
Current numbers:
Spend:
Conversions:
CPA/CAC:
Revenue/ROAS:
Confidence in tracking:
Classification:
[stop / repair / learn / scale]
Diagnosis:
| Area | Finding | Evidence | Severity | Next move |
Budget moves:
- Increase:
- Hold:
- Cut:
Tests:
1. [test]
2. [test]
3. [test]
Data needed before scaling:
- [missing signal]
What ships with it
1 file 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 · 79 lines · 38 tokens per session scan A a561a55d7ed4
paid-ads is a skill published in the GitHub repository Infinite-Labs-AI/infinite-skills (44 stars, last pushed 2mo ago), licensed MIT. It adds 38 tokens to every session and 478 once invoked, about $0.0002 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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