ad-spend-optimizer

ad-spend-optimizer is a skill for Claude Code, Codex from guia-matthieu/clawfu-skills. It costs 87 tokens per session (1,396 once invoked), scanned A, original, MIT.

A method for reviewing paid advertising results across channels such as Google Ads, Meta, or LinkedIn. It calculates measures including ROAS, which compares advertising revenue with spend, and CAC, the cost of acquiring a customer.

In plain words
What is it for?
Use it for quarterly budget planning, comparing channels, investigating poor performance, deciding whether to scale a channel, and planning tests for new channels.
Why use it?
It helps identify where additional budget may produce better returns and where spending is becoming less effective. It also helps explain rising customer-acquisition costs or falling returns.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: positional $N argument.

Good fit Use it for quarterly budget planning, comparing channels, investigating poor performance, deciding whether to scale a channel, and planning tests for new channels.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/guia-matthieu/clawfu-skills/ad-spend-optimizer
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add guia-matthieu/clawfu-skills --skill ad-spend-optimizer
Clone the repo
git clone --depth 1 https://github.com/guia-matthieu/clawfu-skills

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for ad-spend-optimizer

README.md
[![agentmods](https://agentmods.dev/badge/skills/guia-matthieu/clawfu-skills/ad-spend-optimizer/github.svg)](https://agentmods.dev/skills/guia-matthieu/clawfu-skills/ad-spend-optimizer)
Your own site
<a href="https://agentmods.dev/skills/guia-matthieu/clawfu-skills/ad-spend-optimizer"><img src="https://agentmods.dev/badge/skills/guia-matthieu/clawfu-skills/ad-spend-optimizer/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for ad-spend-optimizer

Your own site · 80×15
<a href="https://agentmods.dev/skills/guia-matthieu/clawfu-skills/ad-spend-optimizer"><img src="https://agentmods.dev/badge/skills/guia-matthieu/clawfu-skills/ad-spend-optimizer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 87 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,396 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00087 $0.01396
Opus 5 $0.00044 $0.00698
Sonnet 5 $0.00017 $0.00279
Haiku 4.5 $0.00009 $0.00140

Measured 11d ago against content hash 02147ca9fe07, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

ad-spend-optimizer scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/acquisition/ad-spend-optimizer/SKILL.md · 147 lines

How it starts

The opening of the file, as written. The whole thing — 147 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Ad Spend Optimizer

Analyze paid advertising performance across channels and recommend budget reallocation to maximize ROAS and minimize CAC.

When to Use This Skill

  • Quarterly budget planning — reallocate spend based on performance data
  • Channel mix optimization — find the right balance across platforms
  • Performance troubleshooting — diagnose why CAC is rising or ROAS declining
  • Scaling decisions — determine if a channel has headroom to scale
  • New channel testing — structure test budgets with clear success criteria

Methodology Foundation

Aspect Details
Source Marginal ROI optimization + portfolio theory for marketing
Core Principle Allocate each dollar where the marginal return is highest — shift spend from diminishing-returns channels to underspent ones
Framework 70/20/10 — 70% proven channels, 20% optimization tests, 10% new channel experiments

What Claude Does vs What You Decide

Claude Does You Decide
Calculates ROAS, CAC, and CPL per channel and campaign Total budget constraints
Identifies diminishing returns and reallocation opportunities Risk tolerance for new channels
Models projected outcomes for different allocation scenarios Business priorities and brand considerations
Creates monitoring dashboards and alert thresholds Platform selection and creative direction

Instructions

Step 1: Audit Current Performance

Collect these metrics per channel and campaign:

Metric Formula Healthy Range
ROAS Revenue ÷ Ad Spend >3:1 for most B2B/B2C
CAC Ad Spend ÷ New Customers <LTV ÷ 3
CPL Ad Spend ÷ Leads Varies by industry
CTR Clicks ÷ Impressions >1% search, >0.5% social
Conv Rate Conversions ÷ Clicks >2% landing pages

Validation checkpoint: If data is missing for any channel, flag it — incomplete data leads to wrong reallocations.

Read the full file on GitHub · 147 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 11d ago First seen · 147 lines · 87 tokens per session scan A 02147ca9fe07

Subscribe to this mod's changes

ad-spend-optimizer is a skill published in the GitHub repository guia-matthieu/clawfu-skills (149 stars, last pushed 5mo ago), licensed MIT. It adds 87 tokens to every session and 1,396 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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