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-strategygit 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-strategy)<a href="https://agentmods.dev/skills/zubair-trabzada/ai-ads-claude/ads-strategy"><img src="https://agentmods.dev/badge/skills/zubair-trabzada/ai-ads-claude/ads-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/zubair-trabzada/ai-ads-claude/ads-strategy"><img src="https://agentmods.dev/badge/skills/zubair-trabzada/ai-ads-claude/ads-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 | $0.00067 | $0.08969 |
| Opus 5 | $0.00034 | $0.04484 |
| Sonnet 5 | $0.00013 | $0.01794 |
| Haiku 4.5 | $0.00007 | $0.00897 |
Grade A, and why
ads-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 13d 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 — 900 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Full Ad Strategy Orchestrator
Skill Purpose
Perform a comprehensive, end-to-end advertising strategy build for any business from a single URL. This is the flagship command of the AI Ads Strategist — it launches 5 parallel subagents simultaneously to analyze every dimension of ad readiness, then synthesizes all findings into a unified strategy document with a composite Ad Readiness Score (0-100).
The output is a client-ready deliverable that covers audience research, creative strategy, funnel architecture, competitive positioning, and budget allocation — the kind of document an agency would charge $3,000-$10,000 to produce.
When to Use
- User runs
/ads strategy <url> - User asks for a "full ad strategy", "complete advertising plan", or "ad audit"
- User wants everything in one command without running individual ad skills separately
- User needs a single deliverable covering all advertising dimensions
- User is preparing to launch paid ads and wants a complete roadmap
Input Requirements
- Required: A business URL to analyze
- Optional: Monthly budget, target geography, industry context, specific platforms of interest
How to Execute
This skill runs 3 phases. Phase 1 gathers intelligence. Phase 2 launches 5 parallel subagents. Phase 3 synthesizes all results into the final report.
Display progress to the user:
================================================================
ADS STRATEGY BUILD: [Company Name]
================================================================
Phase 1: Discovery & Business Intelligence ......... [running]
Phase 2: Parallel Agent Analysis ................... [pending]
- Audience Research Agent (25%) .................. [pending]
- Creative Strategy Agent (20%) .................. [pending]
- Funnel Architecture Agent (20%) ................ [pending]
- Competitive Intelligence Agent (15%) ........... [pending]
- Budget & ROI Agent (20%) ...................... [pending]
Phase 3: Synthesis & Report Generation ............. [pending]
================================================================
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.
- 13d ago First seen · 900 lines · 67 tokens per session scan A 063d84389fdc
ads-strategy is a skill published in the GitHub repository zubair-trabzada/ai-ads-claude (246 stars, last pushed 5mo ago), licensed MIT. It adds 67 tokens to every session and 8,969 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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