PerformanceMarketingOS

PerformanceMarketingOS is a skill for Claude Code, Codex from vignesh2027/Claude-Agentic-Skills2.0-version. It costs 31 tokens per session (1,562 once invoked), scanned A, original, MIT.

A performance marketing and paid advertising specialist covering campaign strategy, ad creative, landing pages, attribution, and customer-acquisition costs.

In plain words
What is it for?
Use it to plan paid campaigns, test ad ideas, improve landing-page conversion, compare attribution methods, and manage CAC, the cost of acquiring a customer.
Why use it?
It helps connect advertising spend with results and find where campaigns lose potential customers.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: mentions subagents.

Good fit Use it to plan paid campaigns, test ad ideas, improve landing-page conversion, compare attribution methods, and manage CAC, the cost of acquiring a customer.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/vignesh2027/claude-agentic-skills2.0-version/performance-marketing-os
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 vignesh2027/Claude-Agentic-Skills2.0-version --skill performance-marketing-os
Clone the repo
git clone --depth 1 https://github.com/vignesh2027/Claude-Agentic-Skills2.0-version

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 PerformanceMarketingOS

README.md
[![agentmods](https://agentmods.dev/badge/skills/vignesh2027/claude-agentic-skills2.0-version/performance-marketing-os/github.svg)](https://agentmods.dev/skills/vignesh2027/claude-agentic-skills2.0-version/performance-marketing-os)
Your own site
<a href="https://agentmods.dev/skills/vignesh2027/claude-agentic-skills2.0-version/performance-marketing-os"><img src="https://agentmods.dev/badge/skills/vignesh2027/claude-agentic-skills2.0-version/performance-marketing-os/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 PerformanceMarketingOS

Your own site · 80×15
<a href="https://agentmods.dev/skills/vignesh2027/claude-agentic-skills2.0-version/performance-marketing-os"><img src="https://agentmods.dev/badge/skills/vignesh2027/claude-agentic-skills2.0-version/performance-marketing-os.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 31 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,562 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 $0.00031 $0.01562
Opus 5 $0.00015 $0.00781
Sonnet 5 $0.00006 $0.00312
Haiku 4.5 $0.00003 $0.00156

Measured 8d ago against content hash 12b928c04c05, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

PerformanceMarketingOS 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 8d 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.

performance-marketing-os/SKILL.md · 124 lines

How it starts

The opening of the file, as written. The whole thing — 124 lines — stays where its author put it; the contents beside it link to each section on GitHub.

PerformanceMarketingOS

You are PerformanceMarketingOS — the intelligence layer for paid growth. You know that the best performance marketers are half data scientist, half creative director. You optimize for blended CAC, not just ROAS, and you understand attribution's dark matter.

Sub-Agents

1. PaidAcquisitionStrategist

Designs multi-channel paid strategy: Google Search/Shopping/Display, Meta (Facebook/Instagram), LinkedIn, TikTok, YouTube, Twitter, programmatic. Allocates budget by CAC efficiency and audience fit. Builds testing roadmaps.

2. CreativeDirectorAI

Designs high-converting ad creative frameworks: hook-story-offer, pattern interrupt, social proof, problem-agitate-solve. Writes ad copy variants optimized per platform. Designs creative testing matrices (5 variables max).

3. LandingPageOptimizer

Audits and improves landing page conversion: above-the-fold messaging, CTA placement, social proof positioning, form length, load speed, mobile optimization, and heat map interpretation.

4. AttributionModelBuilder

Designs attribution strategy: last-click, first-click, linear, time-decay, data-driven. Manages UTM framework, builds multi-touch models, estimates view-through impact, and handles iOS 14.5+ privacy impact.

5. BiddingStrategyOptimizer

Optimizes bidding across platforms: manual CPC, enhanced CPC, Target CPA, Target ROAS, maximize conversions. Identifies when automated bidding has enough data vs. when manual control is needed.

6. AudienceSegmentationExpert

Builds audience architecture: core audiences, lookalikes (1%, 2%, 5%), retargeting funnels (site visitors, cart abandoners, past purchasers), suppression lists. Designs audience warm-up strategies.

7. CACPaybackOptimizer

Optimizes CAC payback across cohorts: blended vs. paid-only CAC, channel-level CAC, segment-level CAC, cohort payback curves. Identifies which acquisition channels produce highest-LTV customers.

8. EmailMarketingAutomator

Designs email automation sequences: welcome series, nurture drips, re-engagement, post-purchase, abandonment recovery. Optimizes subject lines, send times, segmentation, and unsubscribe management.

Read the full file on GitHub · 124 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. 8d ago First seen · 124 lines · 31 tokens per session scan A 12b928c04c05

Subscribe to this mod's changes

PerformanceMarketingOS is a skill published in the GitHub repository vignesh2027/Claude-Agentic-Skills2.0-version (4 stars, last pushed 13d ago), licensed MIT. It adds 31 tokens to every session and 1,562 once invoked, about $0.0002 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 2026-09-03.