Kai Retarget logo

Kai Retarget

Community
cgallic
kai-retarget

Design retargeting and remarketing campaign architecture across platforms — audience segmentation, creative strategy, frequency caps, and platform-specific setup with ad policy compliance. Use when "retargeting", "remarketing", "retarget", "re-engage visitors", "abandoned cart", "pixel setup", or any request to bring back visitors who didn't convert.

Overview

Publishercgallic
Repositorykai-cmo-harness
Skill namekai-retarget
Stars
61
Forks
8
Bundled files
Instructions only
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by cgallic on GitHub. Read the source before you install it.

Installation

Install the Kai Retarget AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/cgallic/kai-cmo-harness/tree/main/harness/skills-v2/kai-retarget
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/cgallic/kai-cmo-harness.git /tmp/kai-cmo-harness
mkdir -p .claude/skills
cp -r /tmp/kai-cmo-harness/harness/skills-v2/kai-retarget .claude/skills/kai-retarget
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Kai Retarget in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Kai Retarget on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Kai Retarget is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Objective

A retargeting architecture that is ready to build in the ad accounts: audience segments defined by intent and recency, creative matched to each segment's intent level, frequency caps, exclusion rules, sequence timing, budget split, and platform-compliant ad copy. The plan states which pixel events and URL rules define each audience, so someone can implement it without guessing.

Retargeting fails in two ways — showing the same ad to everyone regardless of how close they got, and showing it so often that it burns the brand. Segmentation and frequency caps exist to prevent both.

Done when

Work type paid-ad-campaign — floor E5/C4/O4 (harness/eco-floors.yaml), spend_authority: true.

  • E5 — the platform returns ad object ids and a read-back of the live entities confirms targeting, budget, schedule, and creative match the approved bundle field for field. Hard stop: live-account mutation without recorded human approval is never SHIPPED, whatever the rest of the evidence shows.
  • C4 — every platform's policy reference was loaded before the ad was written and the ad was checked against it; Four U's at 10/16 (ad threshold), banned_word_check clean, mutation_risk_lint clean; frequency caps set per segment; converters and exclusion lists verified in place. Max 2 auto-retry cycles, each naming the specific failure.
  • O4 — CAC, CPL, ROAS, or qualified-lead rate against a threshold declared before launch, read from the ads connector no earlier than the conversion window plus learning phase. Platform-reported ROAS is not attribution; a holdout or geo-split is what supports O5 (knowledge/frameworks/marketing-science/attribution-and-incrementality.md).

Constraints

  • Read MARKETING.md from the project root first. If it does not exist, build it from the codebase — CLAUDE.md, README.md, PROJECT.md, package.json, landing pages, email/ad/analytics config — using the template from /kai-email-system, and confirm the draft. Do not ask the user what the product is.
  • Seven things must be known before designing segments: traffic sources; conversion points that matter; where drop-off happens; which platforms have pixels or tags installed; monthly retargeting budget; which platforms to run; and product shape (B2B or B2C, high-ticket or impulse, long or short sales cycle).
  • Load the policy reference for every active platform before writing a single line of ad copy. Compliance is not a review step applied afterward.
  • Exclude converters from every retargeting pool. Also suppress existing customers, employees, and competitors.
  • Frequency caps are mandatory per segment — typically 3–5 impressions/day maximum.
  • Segment by intent level, not just by "visited the site": homepage visitors, pricing or product viewers, and cart or form abandoners are three different audiences with three different messages. Set recency windows at 1–3, 3–7, 7–30, and 30–90 days.
  • Budget skews toward higher intent, and copy respects each platform's character limits and format rules.
  • No live-account mutation. This skill produces the plan and the copy; building or editing audiences, budgets, and creative in a live account goes through human approval first.

Context

NeedLoad
Retargeting and remarketing mechanicsknowledge/playbooks/retargeting-remarketing.md
FTC, GDPR consent, pixel and tracking lawharness/references/advertising-compliance.md
Ad copy structural guardrailsharness/references/ad-write-guardrails.md
Paid ad format contract and gate minimumsharness/skill-contracts/meta-ads.yaml
Product, ICP, voice, current channelsMARKETING.md (project root)

Platform policy — load the row for each active platform before writing:

PlatformReference
Metaharness/references/meta-ads-rules.md
Googleharness/references/google-ads-policy-reference.md
LinkedInharness/references/linkedin-ads-rules.md
TikTokharness/references/tiktok-ads-policy-reference.md
Microsoft/Bingharness/references/microsoft-ads-rules.md
Pinterestharness/references/pinterest-ads-rules.md
Snapchatharness/references/snapchat-ads-policy-reference.md
Amazonharness/references/amazon-ads-policy-reference.md
X/Twitterharness/references/x-ads-policy-reference.md

Creative by intent level:

SegmentSignalMessage
Low intentHomepage visitorsBrand awareness, social proof
Medium intentProduct or pricing viewersValue props, comparison, objection handling
High intentCart or form abandonersUrgency, incentive, friction removal

Deliver: campaign architecture (segments, creative, timing), platform-ready audience definitions (pixel events, URL rules, time windows), ad copy per segment per platform, budget allocation table, frequency cap settings, exclusion rules, a per-platform policy compliance checklist, and the gate pass/fail summary.

Output goes to workspace/ as retarget-campaign-YYYY-MM-DD.md. Same path as v1.

Escalate when

  • Pixels or conversion tags are missing on a platform the plan depends on.
  • Drop-off data does not exist, so segments would be guessed rather than observed, or consent basis for tracking is unresolved in a jurisdiction the audience covers.
  • The product falls in a Special Ad Category (housing, employment, credit) or another restricted vertical where retargeting is limited or banned.
  • Budget is too small to sustain frequency across the proposed segment count.
  • Anyone asks for the campaign to be built or edited in a live account without recorded approval.

Frequently asked questions

What does the Kai Retarget AI skill do?

Design retargeting and remarketing campaign architecture across platforms — audience segmentation, creative strategy, frequency caps, and platform-specific setup with ad policy compliance. Use when "retargeting", "remarketing", "retarget", "re-engage visitors", "abandoned cart", "pixel setup", or any request to bring back visitors who didn't convert.

Why use Kai Retarget on TypingMind?

Because you install it once and use it with any model. Kai Retarget is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Kai Retarget in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/cgallic/kai-cmo-harness/tree/main/harness/skills-v2/kai-retarget. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Kai Retarget?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Kai Retarget?

As many as you like. As long as a model supports skills, you can use Kai Retarget with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Kai Retarget AI skill free?

It is published on GitHub by cgallic. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇