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/yahav123147-ads-math
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: backend, data, marketing, finance
Reviews
Write a reviewNo reviews yet. Installed it? Reviews come from verified installers only. How reviews work
Permissions
What this skill can do and what it asks for, from its SKILL.md. 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-math
What's inside
- Skill name
ads-math- Description
- PPC financial calculator and modeling tool. CPA, ROAS, CPL calculations, break-even analysis, impression share opportunity sizing, budget forecasting, LTV:CAC ratio analysis, and MER (Marketing Efficiency Ratio) assessment. Requires zero API access. Works with pasted data from exports. Use when user says PPC math, ad calculator, break-even, budget forecast, ROAS calculator, CPA calculator, impression share, LTV CAC, or MER.
- License
- MIT
- Instructions
- 211 lines in SKILL.md · view on GitHub
Files (1)
- SKILL.md
SKILL.md (first lines)
# PPC Financial Calculator & Modeling <!-- Created: 2026-04-13 | v1.5 --> <!-- Source: itallstartedwithaidea/google-ads-skills (PPC math concept) --> ## Process 1. Ask the user what calculation they need (or detect from context) 2. Collect required inputs (from pasted data, exports, or verbal description) 3. Perform calculations with clear formulas shown 4. Present results with interpretation and recommendations 5. Flag any concerning metrics or benchmarks ## Calculators ### 1. CPA Calculator ``` CPA = Total Spend / Total Conversions Inputs needed: - Total ad spend (period) - Total conversions (same period) Output: - CPA with period context - CPA trend (if historical data provided) - Comparison to industry benchmark (from benchmarks.md) ``` ### 2. ROAS Calculator ``` ROAS = Revenue from Ads / Ad Spend ROAS% = (Revenue - Spend) / Spend × 100 Inputs needed: - Total ad spend - Total revenue attributed to ads Output: - ROAS as ratio (e.g., 3.5x) and percentage (250%) - Break-even ROAS (based on margins if provided) - Comparison to platform benchmarks ``` ### 3. Break-Even Analysis ``` Break-Even CPA = Average Order Value × Profit Margin Break-Even ROAS = 1 / Profit Margin Inputs needed: - Average order value (AOV) OR average deal value - Profit margin (gross margin %) - Current CPA or ROAS Output: - Maximum profitable CPA - Minimum profitable ROAS - Current headroom (how far above/below break-even) - Recommendation: scale, maintain, or cut ``` ### 4. Impression Share Opportunity ``` Impression Share Lost (Budget) = opportunity from budget increase Impression Share Lost (Rank) = opportunity from bid/quality improvement Revenue Opportunity = Current Revenue × (1 / Current IS - 1) Inputs needed: - Current impression share % - IS lost to budget % - IS lost to rank % - Current spend and conversions Output: - Estimated additional conversions from full IS - Budget needed for full IS (estimated) - Priority: budget increase vs quality improvement ``` ### 5. Budget Forecasting ``` Projected Spend = Daily Budget × Days in Period Projected Conversions = Projected Spend / Historical CPA Projected Revenue = Projected Conversions × AOV Scaling scenarios: - Conservative: +20% budget → estimated impact - Moderate: +50% budget → estimated impact - Aggressive: +100% budget → estimated impact (with diminishing returns caveat) Inputs needed: - Current daily budget - Historical CPA (last 30 days) - Forecast period - AOV (if revenue projection needed) Output: - 3 scenarios with spend, conversions, revenue projections - Diminishing returns warning for aggressive scaling - 20% scaling rule reminder (never increase >20% at a time) ``` ### 6. LTV:CAC Ratio ``` CAC = Total Marketing Spend / New Customers Acquired LTV = Average Revenue per Customer × Average Customer Lifespan LTV:CAC Ratio = LTV / CAC Inputs needed: - Total marketing spend (all channels) - New customers acquired - Average revenue per customer (monthly or annual)
From yahav123147/paid-ads-cro-skills, MIT.
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Signals
- Stars
- 0
- Forks
- 1
- Open issues
- 0
- Last commit (this folder)
- May 13, 2026 (5 months ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- MIT
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
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Cite this page
ads-math skill. Agent Mart. https://agentmart.dev/skills/yahav123147-ads-math (last updated 2026-10-24)