ads-math
Skill102 starsChanged 6 months agoMITView on GitHub
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.
4 other projects use a version of this, 3 of them edited.
Adopted by
Most recently taken up by
- oivanfelipe/claude-skillsedited, first seen Nov 8, 2026
- AgriciDaniel/claude-adstheir own version, first seen Oct 25, 2026
- chriswestt/claude-skillsedited, first seen Oct 9, 2026
- Maxymize/maxym-ai-adsedited, first seen Apr 21, 2026
Other versions4 projects use a version of this.
Word for word · 0
None found.
Edited · 3
- Maxymize/maxym-ai-ads★ 297% same
- chriswestt/claude-skills★ 097% same
- oivanfelipe/claude-skills★ 099% same
Wrote their own version · 1
- AgriciDaniel/claude-ads★ 10ksame name
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository21 other files it gives its agents.
- CLAUDE.mdCLAUDE.md
- adsSkill
- ads-auditSkill
- ads-budgetSkill
- ads-competitorSkill
- ads-concienciaSkill
- ads-createSkill
- ads-creativeSkill
- ads-dnaSkill
- ads-generateSkill
- ads-googleSkill
- ads-landingSkill
- ads-metaSkill
- ads-nextSkill
- ads-photoshootSkill
- ads-planSkill
- ads-publishSkill
- ads-startSkill
- ads-testSkill
- ads-tiktokSkill
- ads-updateSkill
The file
We split this skill into the rules it gives an agent
2 rules. 2 are common, 0 are distinctive, and 0 are very specific to this project.
2
Common
Most of the 4 edited versions we read keep these.
0
Distinctive
This author's own choices. Worth a look.
0
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Common: line 14
Ask the user what calculation they need (or detect from context)
- Common: line 209
If the user doesn't provide enough data, ask for:
“Common” is measured: kept by at least 6 in 10 of the 4 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
<!-- Portions Copyright (c) 2026 Enrique Rocha (@soyenriquerocha) - see LICENSE for original authors · tododeia.com · id er-fd4fa55b -->PPC Financial Calculator & Modeling
Concept adapted from
itallstartedwithaidea/google-ads-skills(PPC math).
Process
- Ask the user what calculation they need (or detect from context)
- Collect required inputs (from pasted data, exports, or verbal description)
- Perform calculations with clear formulas shown
- Present results with interpretation and recommendations
- 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 benchmarks3. 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 cut4. 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 improvement5. 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)
- Average customer lifespan (months)
- Optional: gross margin for unit economics
Output:
- LTV:CAC ratio with interpretation:
- <1:1 = losing money on every customer
- 1:1-2:1 = break-even to marginal
- 3:1 = healthy (SaaS benchmark)
- 5:1+ = may be under-investing in growth
- Payback period: months to recover CAC
- Recommendation based on ratio7. MER (Marketing Efficiency Ratio)
MER = Total Revenue / Total Marketing Spend
Inputs needed:
- Total business revenue (period)
- Total marketing spend across ALL channels (same period)
Output:
- MER ratio (e.g., 5.0x)
- Interpretation:
- E-commerce: 3-5x typical, 8x+ excellent
- SaaS: 5-10x typical (higher margins)
- Local service: 3-8x typical
- Comparison to business-type benchmark
- Note: MER captures blended efficiency including organic, brand, and retentionIncrementality & Advanced Measurement
For advanced accounts evaluating cross-channel contribution:
- Meta Incremental Attribution (launched April 2025): AI-powered holdout testing measuring real causal impact. Evaluate if budget exceeds $5K/month.
- Google Meridian (2025): Open-source Marketing Mix Model for incrementality measurement across channels.
- These tools complement PPC math calculations by measuring what would NOT have happened without the ad spend.
For large accounts detecting small effects (5% MDE), multiply the 10% MDE sample by ~4x.
Quick Formulas Reference
| Metric | Formula |
| CPA | Spend / Conversions |
| ROAS | Revenue / Spend |
| CTR | Clicks / Impressions × 100 |
| CVR | Conversions / Clicks × 100 |
| CPC | Spend / Clicks |
| CPM | (Spend / Impressions) × 1,000 |
| CPL | Spend / Leads |
| Break-Even CPA | AOV × Margin% |
| Break-Even ROAS | 1 / Margin% |
| LTV | ARPU × Avg Lifespan |
| CAC | Total Marketing / New Customers |
| MER | Total Revenue / Total Marketing |
| Impression Share Opp | Revenue × (1/IS - 1) |
Output Format
## PPC Financial Analysis
### [Calculator Name]
**Inputs:**
- [Listed inputs with values]
**Results:**
| Metric | Value | Benchmark | Status |
|--------|-------|-----------|--------|
| [Metric] | [Value] | [Benchmark] | PASS/WARNING/FAIL |
**Interpretation:**
[1-2 sentence analysis]
**Recommendation:**
[Actionable next step]Data to Request
If the user doesn't provide enough data, ask for:
- Platform and campaign type
- Time period for analysis
- Spend and conversion data
- Revenue data (if ROAS/break-even needed)
- Margin data (if break-even/LTV needed)
- Business type (for benchmark comparison)
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

