Install
$ agentstack add skill-cgallic-kai-cmo-harness-kai-retarget ✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.
Security review
✓ PassedNo issues found. Passed automated security review. · v0.1.0 How review works →
- ✓ Prompt-injection patterns
- ✓ Secret / credential exfiltration
- ✓ Dangerous shell & filesystem operations
- ✓ Untrusted network calls
- ✓ Known-malicious package signatures
What it can access
- ✓ Network access No
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ✓ Environment & secrets No
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
Verified badge
Passed review? Show it. Paste this badge into your README, it links to the public security report.
Reliability & compatibility
Declared compatibility
Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.
We're building live execution health for every listing: tool-call success rate, median latency, uptime, and last-checked timestamps, measured, not self-reported. It isn't live yet, so we don't show numbers we can't stand behind.
How agent discovery & health will work →About
Kai Retarget Skill
Design retargeting/remarketing campaign architecture across platforms with audience segmentation, creative strategy, and policy compliance.
Phase 0: Load Product Context
Check if MARKETING.md exists in the project root (same directory as CLAUDE.md, README.md, package.json).
If it exists: Read it — skip product discovery questions. It has the product name, ICP, value prop, monetization, brand voice, current channels, and competitive landscape.
If it does NOT exist: Auto-explore the codebase to create it in the project root (next to CLAUDE.md). Do NOT ask the user what the product is. Read CLAUDE.md, README.md, PROJECT.md, package.json, landing pages, and any project files. Search for email/ad/analytics config. Then create MARKETING.md using the template from /kai-email-system. Present draft to user for confirmation.
Phase 1: Discovery
Read from MARKETING.md. Only ask about things not covered there:
- Traffic sources — Where do visitors come from? (organic, paid, social, email)
- Conversion points — What actions matter? (purchase, signup, demo, download)
- Drop-off data — Where do people leave? (homepage, pricing, checkout, form)
- Pixel/tag status — Which platforms have tracking installed?
- Budget — Monthly retargeting spend available
- Platforms — Which ad platforms to retarget on? (Meta, Google, LinkedIn, TikTok, etc.)
- Product type — B2B or B2C? High-ticket or impulse? Long or short sales cycle?
Phase 2: Plan
Build the retargeting architecture:
- Load retargeting playbook:
E:\Dev2\kai-cmo-harness-work\knowledge\playbooks\retargeting-reMARKETING.md - Load platform policy references (for each active platform):
- Meta:
E:\Dev2\kai-cmo-harness-work\harness\references\meta-ads-rules.md - Google:
E:\Dev2\kai-cmo-harness-work\harness\references\google-ads-policy-reference.md - LinkedIn:
E:\Dev2\kai-cmo-harness-work\harness\references\linkedin-ads-rules.md - TikTok:
E:\Dev2\kai-cmo-harness-work\harness\references\tiktok-ads-policy-reference.md - Microsoft:
E:\Dev2\kai-cmo-harness-work\harness\references\microsoft-ads-rules.md - Pinterest:
E:\Dev2\kai-cmo-harness-work\harness\references\pinterest-ads-rules.md - Snapchat:
E:\Dev2\kai-cmo-harness-work\harness\references\snapchat-ads-policy-reference.md - Amazon:
E:\Dev2\kai-cmo-harness-work\harness\references\amazon-ads-policy-reference.md - X/Twitter:
E:\Dev2\kai-cmo-harness-work\harness\references\x-ads-policy-reference.md
- Load compliance framework:
E:\Dev2\kai-cmo-harness-work\harness\references\advertising-compliance.md - Define audience segments:
- Segment by intent level (visited homepage vs. visited pricing vs. started checkout)
- Set recency windows (1-3 days, 3-7 days, 7-30 days, 30-90 days)
- Exclude converters from retargeting pools
- Map creative to segment — Different message for each intent level
- Set frequency caps — Prevent ad fatigue (typically 3-5 impressions/day max)
- Define exclusion rules — Suppress ads for existing customers, employees, competitors
Phase 3: Produce
Build the campaign assets:
- Audience definitions — Platform-ready segment specs (pixel events, URL rules, time windows)
- Creative briefs per segment:
- Low intent (homepage visitors): Brand awareness, social proof
- Medium intent (product/pricing viewers): Value props, comparison, objection handling
- High intent (cart/form abandoners): Urgency, incentive, friction removal
- Ad copy per platform — Respect character limits and format rules per platform
- Sequence timing — When each segment sees each creative
- Budget allocation — Higher spend on higher-intent segments
Phase 4: Quality Gates
Validate before launch:
- Four U's Score (on ad copy):
python E:\Dev2\kai-cmo-harness-work\scripts\quality_gates\four_us_score.py
- Minimum: 10/16 (ad threshold)
- Banned Word Check:
python E:\Dev2\kai-cmo-harness-work\scripts\quality_gates\banned_word_check.py - Platform policy compliance — Check each ad against its platform's TOS
- Frequency cap validation — Confirm caps are set per segment
- Exclusion list verification — Confirm converters are excluded
Max 2 auto-retry cycles on gate failures.
Phase 5: Output
Deliver the retargeting package:
- Campaign architecture diagram (segments, creative, timing)
- Audience segment definitions (platform-ready specs)
- Ad copy per segment per platform
- Budget allocation table
- Frequency cap settings
- Exclusion rules
- Policy compliance checklist (per platform)
- Gate pass/fail summary
Write output to E:\Dev2\kai-cmo-harness-work\workspace\ with filename pattern: retarget-campaign-YYYY-MM-DD.md
Source & license
This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: cgallic
- Source: cgallic/kai-cmo-harness
- License: MIT
- Homepage: https://meetkai.xyz
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.