ads
When the user wants help with paid advertising campaigns on Google Ads, Meta (Facebook/Instagram), LinkedIn, Twitter/X, or other ad platforms.
Skill by lukemcqueen
Install
Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.
npx agentmarket install skill/lukemcqueen-ads
Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.
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About
Use cases: marketing, sales, finance
Reviews
Write a reviewNo reviews yet. Installed it? Reviews come from verified installers only. How reviews work
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What this skill can do and what it asks for, from its SKILL.md and code. Checked Oct 25, 2026.
- Tools
- No tools found
- Secrets
- None asked for
- Install scripts
- None found
Network hosts it talks to 1
codeload.github.com· found in install command
Files it touches
~/.claude/skills/ads
What's inside
- Skill 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.
- License
- MIT
- Metadata
- version: 2.2.0
- Instructions
- 482 lines in SKILL.md · view on GitHub
Files (11)
- SKILL.md
- abm-playbook.md · references/
- ad-copy-templates.md · references/
- audience-targeting.md · references/
- b2b-paid-playbook.md · references/
- conversion-tracking.md · references/
- google-search-playbook.md · references/
- linkedin-b2b-playbook.md · references/
- meta-decision-system.md · references/
- platform-setup-checklists.md · references/
- rsa-output-spec.md · references/
SKILL.md (first lines)
# 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 | |---|---|---| | 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 | [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 | | 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 | | 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 | | **Twitter/X** | Tech audiences, thought leadership | Audience is active on X, timely content | | **TikTok** | Younger demographics, viral creative | Audience skews 18-34, video capacity | --- ## Campaign Structure Best Practices ### Account Organization ``` Account ├── Campaign 1: [Objective] - [Audience/Product] │ ├── Ad Set 1: [Targeting variation] │ │ ├── Ad 1: [Creative variation A] │ │ ├── Ad 2: [Creative variation B] │ │ └── Ad 3: [Creative variation C] │ └── Ad Set 2: [Targeting variation] └── Campaign 2... ``` ### Naming Conventions ``` [Platform]_[Objective]_[Audience]_[Offer]_[Date] Examples: META_Conv_Lookalike-Customers_FreeTrial_2024Q1 GOOG_Search_Brand_Demo_Ongoing LI_LeadGen_CMOs-SaaS_Whitepaper_Mar24 ``` ### Budget Allocation **Testing phase (first 2-4 weeks):** - 70% to proven/safe campaigns - 30% to testing new audiences/creative **Scaling phase:** - Consolidate budget into winning combinations - Increase budgets ~20% at a time — never 30%+ in one move (resets platform learning) - Wait 3-5 days between increases for algorithm learning --- ## Ad Copy Frameworks ### Key Formulas **Problem-Agitate-Solve (PAS):** > [Problem] → [Agitate the pain] → [Introduce solution] → [CTA] **Before-After-Bridge (BAB):** > [Current painful state] → [Desired future state] → [Your product as bridge] **Social Proof Lead:** > [Impressive stat or testimonial] → [What you do] → [CTA] **For detailed templates and headline formulas**: See [references/ad-copy-templates.md](references/ad-copy-templates.md) ---
From lukemcqueen/hermes-cortex, MIT.
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Compare and alternatives
Featured in
Signals
- Stars
- 4
- Forks
- 1
- Open issues
- 1
- Last commit (this folder)
- Oct 22, 2026 (5 days ago)
From GitHub (fetched Oct 24, 2026).
Details
- Version
- 2.2.0
- License
- MIT
- Repository
- github.com/lukemcqueen/hermes-cortex
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
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Cite this page
ads skill. Agent Mart. https://agentmart.dev/skills/lukemcqueen-ads (last updated 2026-10-24)