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 zubair-trabzada/ai-ads-claude --skill ads-quickgit clone --depth 1 https://github.com/zubair-trabzada/ai-ads-claudeWrote 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/zubair-trabzada/ai-ads-claude/ads-quick)<a href="https://agentmods.dev/skills/zubair-trabzada/ai-ads-claude/ads-quick"><img src="https://agentmods.dev/badge/skills/zubair-trabzada/ai-ads-claude/ads-quick/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/zubair-trabzada/ai-ads-claude/ads-quick"><img src="https://agentmods.dev/badge/skills/zubair-trabzada/ai-ads-claude/ads-quick.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 | $0.00017 | $0.02551 |
| Opus 5 | $0.00009 | $0.01275 |
| Sonnet 5 | $0.00003 | $0.00510 |
| Haiku 4.5 | $0.00002 | $0.00255 |
Grade A, and why
ads-quick 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 12d 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 — 216 lines — stays where its author put it; the contents beside it link to each section on GitHub.
60-Second Ad Readiness Snapshot
Skill Purpose
Perform a rapid ad readiness assessment of a website or business without launching subagents. Fetches the homepage, evaluates value proposition strength, offer clarity, CTA quality, landing page readiness, and trust signal presence. Outputs a compact scorecard with a platform recommendation and estimated starting budget. The entire output must be under 40 lines.
When to Use
- User wants a quick gut-check before investing in a full ad strategy
- User asks "should I run ads?" or "am I ready for ads?"
- User wants a fast assessment without waiting for the full 5-agent analysis
- User is exploring whether paid advertising makes sense for their business
- Triggered by
/ads quick <url>
When NOT to Use
- User wants a detailed, comprehensive strategy (use
/ads strategyinstead) - User already has ad data to analyze (use
/ads auditinstead) - User needs creative briefs (use
/ads creativeinstead) - No URL is provided (this skill requires a URL to fetch)
How to Execute
Step 1: Fetch and Analyze the Homepage
Use WebFetch to retrieve the homepage content. Extract these elements:
WebFetch(url) -> Analyze:
1. Headline / Hero Section — What is the main promise?
2. Value Proposition — Is it clear what they sell and why it matters?
3. CTA(s) — What action are they asking visitors to take?
4. Offer — Is there a specific offer (pricing, free trial, discount)?
5. Trust Signals — Reviews, testimonials, badges, client logos, certifications?
6. Visual Quality — Professional images, consistent branding, modern design?
7. Mobile Indicators — Responsive hints, fast-loading signals?
8. Contact Info — Phone, email, chat, address visible?
Step 2: Score 5 Dimensions
Rate each dimension on a 0-20 scale:
1. Value Proposition Strength (0-20)
| Score | Criteria |
|---|---|
| 17-20 | Crystal clear what they do, for whom, and why it's better. Unique mechanism stated. |
| 13-16 | Clear offering, target audience implied, some differentiation. |
| 9-12 | Generic value prop, could apply to many businesses. |
| 5-8 | Vague or buried value proposition. Requires effort to understand. |
| 0-4 | No clear value proposition. Visitor would not know what this business does. |
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.
- 12d ago First seen · 216 lines · 17 tokens per session scan A 7e5d380f96f9
ads-quick is a skill published in the GitHub repository zubair-trabzada/ai-ads-claude (245 stars, last pushed 5mo ago), licensed MIT. It adds 17 tokens to every session and 2,551 once invoked, about $0.0001 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.
Other skills, from other repositories
realestate-quick
60-Second Property Snapshot — quick assessment without subagents for fast property evaluation with signal, key factors, and CTA for full analysis.
recruit-quick
60-Second Role Snapshot — quick assessment without subagents with grade, top 3 fixes, and CTA to full analysis.
restaurant-quick
60-Second Restaurant Snapshot — quick assessment without subagents with grade, top 3 fixes, and CTA to full audit.
crypto-quick
60-Second Token Snapshot — fast assessment with signal, key factors, and price levels without launching subagents.
recruit-quick
60-Second Role Snapshot — quick assessment without subagents with grade, top 3 fixes, and CTA to full analysis.
ad-campaign-analyzer
Analyze cross-channel campaign data, quantify uncertainty, and propose evidence-labeled budget tests without overstating causality.