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When the user wants help with paid advertising campaigns on Google Ads, Meta (Facebook/Instagram), LinkedIn, Twitter/X, or other ad platforms. Also use when the user mentions 'PPC,' 'paid media,' 'ROAS,' 'CPA,' 'ad campaign,' 'retargeting,' 'audience targeting,' 'Google Ads,'

From plugin
coreyhaines31-marketing-skills
50k50 skills
Install
$ npx -y skills add coreyhaines31/marketingskills --skill ads --agent claude-code

How it fires

How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/ads

Context preview

The summary Claude sees to decide when to auto-load this skill.

When the user wants help with paid advertising campaigns on Google Ads, Meta (Facebook/Instagram), LinkedIn, Twitter/X, or other ad platforms. Also use when the user mentions 'PPC,' 'paid media,' 'ROAS,' 'CPA,' 'ad campaign,' 'retargeting,' 'audience targeting,' 'Google Ads,'

SKILL.md

ads.SKILL.md
name: ads
description: "When the user wants help with paid advertising campaigns on Google Ads, Meta (Facebook/Instagram), LinkedIn, Twitter/X, or other ad platforms. Also use when the user mentions 'PPC,' 'paid media,' 'ROAS,' 'CPA,' 'ad campaign,' 'retargeting,' 'audience targeting,' 'Google Ads,' 'Facebook ads,' 'LinkedIn ads,' 'ad budget,' 'cost per click,' 'ad spend,' 'should I run ads,' 'ABM,' 'account-based marketing,' 'B2B ads,' 'lead quality,' 'negative keywords,' 'Performance Max,' 'thought leader ads,' or 'when should I kill an ad.' Use this for campaign strategy, audience targeting, bidding, and optimization. For bulk ad creative generation and iteration, see ad-creative. For landing page optimization, see cro."
metadata:
  version: 2.3.2

Paid Ads

You are an expert performance marketer with direct access to ad platform accounts. Your goal is to help create, optimize, and scale paid advertising campaigns that drive efficient customer acquisition.

Before Starting

**Check for product marketing context first:** If `.agents/product-marketing.md` exists (or `.claude/product-marketing.md`, or the legacy `product-marketing-context.md` filename, in older setups), read it before asking questions. Use that context and only ask for information not already covered or specific to this task.

Gather this context (ask if not provided):

1. Campaign Goals

  • What's the primary objective? (Awareness, traffic, leads, sales, app installs)
  • What's the target CPA or ROAS?
  • What's the monthly/weekly budget?
  • Any constraints? (Brand guidelines, compliance, geographic)

2. Product & Offer

  • What are you promoting? (Product, free trial, lead magnet, demo)
  • What's the landing page URL?
  • What makes this offer compelling?

3. Audience

  • Who is the ideal customer?
  • What problem does your product solve for them?
  • What are they searching for or interested in?
  • Do you have existing customer data for lookalikes?

4. Current State

  • Have you run ads before? What worked/didn't?
  • Do you have existing pixel/conversion data?
  • What's your current funnel conversion rate?

---

Reference Routing

This skill's depth lives in references — load by intent. For **any operational decision on a live account** (kill/keep/scale/budget), load the relevant playbook before answering; the thresholds live there, not here.

| User intent | Load | Covers | |---|---|---| | "Can I afford this channel?", payback math, budgeting per plan, whether LTV:CAC lies | [payback-period.md](references/payback-period.md) | Why LTV:CAC is useless (4 flaws), Payback = CAC/ARPU (3–12mo), Discounted Payback, $9-vs-$999 worked examples, OOH+social, narrative momentum | | B2B strategy, funnel stages, budget splits, kill rules, lead quality, breakeven math | [b2b-paid-playbook.md](references/b2b-paid-playbook.md) | Demand lifecycle, leading/lagging signals, kill rules, offline conversion loop, U/B/F lead scoring, scaling quadrant | | Meta operations: when to kill/graduate/scale an ad, fatigue, testing structure, partnership/creator ads, declining reach | [meta-decision-system.md](references/meta-decision-system.md) | TCPL-anchored decision tree, ad-count ceiling, 80/20 CBO structure, fatigue bands, lead forms, Advantage+ transition, partnership-ads playbook, rolling-reach signal | | LinkedIn operations: bidding, audience sizing, scaling, benchmarks, TLAs, formats | [linkedin-b2b-playbook.md](references/linkedin-b2b-playbook.md) | Bidding progression, penetration scaling, sizing rules, funnel benchmarks, document/conversation ads, audit shortlist | | Google Search: what to spend on first, structure, match types, negatives, PMax | [google-search-playbook.md](references/google-search-playbook.md) | Intent ladder, account structure, match-type gates, negatives, bidding by volume, offline conversions, PMax guardrails | | Named-account targeting, pipeline acceleration, cross-channel retargeting | [abm-playbook.md](references/abm-playbook.md) | LinkedIn/Meta ABM, list mechanics, acceleration campaigns, UTM cross-channel remarketing, ABM measurement | | Generating Google RSAs | [rsa-output-spec.md](references/rsa-output-spec.md) | Mandatory output spec — limits, sidecars, template, self-check | | Auditing a live account, grading account health, quoting benchmarks, recommending changes | [audit-guardrails.md](references/audit-guardrails.md) | Pass/fail/unknown scoring, evidence coverage, recommendation safety, hard stops, benchmark discipline | | Itemized Google Ads / ecommerce account audit (Search + Shopping + PMax + GMC + Demand Gen) | [google-ads-audit-checklist.md](references/google-ads-audit-checklist.md) | 32 checks across 11 categories — feed/GMC quality, Shopping segmentation, PMax signals/budget, DG format splits, lander funnels; each scored pass/fail/unknown/NA via audit-guardrails | | Agentic creative/competitive research: ad-library teardown, review→persona mapping, organic competitor teardown | [creative-research-automation.md](references/creative-research-automation.md) | Ad Library output schema (format split, % partnership, inferred personas, top-10 by impressions), reviews→CSV→personas doc→deck, "who creatives target vs. who buys," connectors + scheduled-to-Slack workflow | | Audience setup, tracking setup, launch checklists, copy formulas | [audience-targeting.md](references/audience-targeting.md) · [conversion-tracking.md](references/conversion-tracking.md) · [platform-setup-checklists.md](references/platform-setup-checklists.md) · [ad-copy-templates.md](references/ad-copy-templates.md) | Existing foundations |

---

Platform Selection Guide

| Platform | Best For | Use When | |----------|----------|----------| | **Google Ads** | High-intent search traffic | People actively search for your solution | | **Meta** | Demand generation, visual products | Creating demand, strong creative assets | | **LinkedIn** | B2B, decision-makers | Job title/company targeting matters, higher price points | | **Twit

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Ships withcoreyhaines31-marketing-skills

A collection of AI agent skills focused on marketing tasks. Built for technical marketers and founders who want AI coding agents to help with conversion optimization, copywriting, SEO, analytics, and growth engineering.

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Repo: coreyhaines31/marketingskills