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ads-math广告数学

Agent Skill

ads-math 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要围绕仓库状态、代码变更或协作事项进行整理时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

3,525

周安装

144

GitHub Stars

3,880

下载量

1,140
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:ads-math(广告数学)
来源仓库:https://github.com/agricidaniel/claude-ads
仓库路径:skills/ads-math
安装命令:
npx skills add https://github.com/agricidaniel/claude-ads --skill ads-math
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/agricidaniel/claude-ads --skill ads-math

简介

ads-math 提供 PPC 财务计算模型,包括 CPA、ROAS 等核心指标分析与趋势解读。

  • 适用于广告预算规划、绩效归因与 ROI 预测等需要量化决策的场景。
  • 支持从导出数据或口头描述中提取输入参数,展示计算公式与行业基准对比。
  • 可处理历史数据以识别趋势,但需用户提供清晰的时间段与数值定义。
  • 建议结合真实投放数据使用,避免因输入错误导致误导性结论。

SKILL.md

PPC Financial Calculator & Modeling

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)
- 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 ratio

7. 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 retention

Incrementality & 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

MetricFormula
CPASpend / Conversions
ROASRevenue / Spend
CTRClicks / Impressions × 100
CVRConversions / Clicks × 100
CPCSpend / Clicks
CPM(Spend / Impressions) × 1,000
CPLSpend / Leads
Break-Even CPAAOV × Margin%
Break-Even ROAS1 / Margin%
LTVARPU × Avg Lifespan
CACTotal Marketing / New Customers
MERTotal Revenue / Total Marketing
Impression Share OppRevenue × (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)

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Claude

33.88%
按下载量换算386

Codex

32.72%
按下载量换算373

Cursor

17.28%
按下载量换算197

Gemini CLI

10.61%
按下载量换算121

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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