performance-marketer

Audit, plan, optimize, and scale paid media campaigns across Meta, Google Ads, TikTok Ads, and Apple Search Ads.

Updated Feb 9, 2026
One-click install
npx skills add https://github.com/HuveD/agent-skillset --skill performance-marketer
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: performance-marketer
Source: https://github.com/HuveD/agent-skillset/tree/main/performance-marketer
Command: npx skills add https://github.com/HuveD/agent-skillset --skill performance-marketer

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

The Performance Marketer OS provides a structured framework to audit, plan, optimize, and scale measurable paid campaigns across major platforms, turning ad operations into repeatable, data-driven processes.

Core Features & Use Cases

  • Evidence-based KPI trees and measurement systems to align team goals with measurable outcomes.
  • Channel-aligned operating model (RACI, cadences, decision logs) to reduce waste and speed decision-making.
  • Continuous monitoring of platform changes and policy updates with proactive optimization actions.
  • Use Case: audit existing campaigns, design a multi-channel plan, and execute a prioritized backlog of experiments to improve roas.

Quick Start

Begin by articulating your north star KPI, set cadences, and run a 2-week measurement readiness check to seed the initial backlog.

Frequently Asked Questions about performance-marketer

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I audit and fix inefficiencies in paid media campaigns across Meta and Google Ads?

To audit paid media campaigns across Meta and Google Ads, use a structured framework to identify inefficiencies and enforce a KPI tree with a measurement plan. This approach turns ad operations into repeatable, data-driven processes to improve ROAS.

What is a KPI tree and how does it align paid media goals with measurable outcomes?

A KPI tree is an evidence-based measurement system that aligns team goals with measurable outcomes for paid campaigns. It connects your north star KPI to specific platform metrics, ensuring all optimization actions directly support overarching performance targets.

How to design a multi-channel paid campaign plan and execute a prioritized experiment backlog?

Design a multi-channel plan by setting cadences and running a measurement readiness check to seed a prioritized experiment backlog. This channel-aligned operating model reduces wasted spend and speeds up decision-making across platforms.

Does this performance marketing framework support TikTok Ads and Apple Search Ads?

Yes, the performance marketing framework supports TikTok Ads and Apple Search Ads. It provides a structured system to audit, plan, optimize, and scale measurable campaigns across these platforms alongside Meta and Google Ads.

Why should I use an evidence-led system instead of ad-hoc campaign optimization?

An evidence-led system prevents wasted budget by enforcing a measurement plan, attribution strategy, and decision logs. Unlike ad-hoc campaign optimization, it establishes clear cadences and a RACI model to speed up decisions and scale ROAS consistently.

What north star KPI do I need to articulate before starting paid campaign optimization?

Before starting paid campaign optimization, you need to articulate your north star KPI and run a two-week measurement readiness check. This initial setup seeds the backlog and ensures your attribution strategy aligns with measurable outcomes.