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Skill evidence / retargeting-funnel
Skill profile

retargeting-funnel

Design a multi-stage retargeting sequence from a site's own funnel data - recency windows and...

What this skill does for you

Design a multi-stage retargeting sequence from a site's own funnel data - recency windows and behavioural-depth tiers per stage, a message and offer ladder for each stage, mutually exclusive audiences with exclusion logic, and per-stage frequency caps. Use whenever the user mentions retargeting or remarketing, cart or form abandonment, how long a retargeting window should be, frequency caps, a retargeting audience that is too small, or ads still showing to people who already bought - even if they never say 'funnel'. Covers B2B and B2C, and produces a stage-by-stage plan rather than campaigns built inside an ad platform. Do NOT use to design cold prospecting audience tiers - use mbfinotti/advertising-skills@ad-audience-targeting instead.

Quoted from the skill description in the pinned source

Who made it

Publishermbfinotti
Installs815as of Sep 27, 2026

Use it with Edge

Set up Edge for me: read getedge.cc/SKILL.md and follow it. Then use Edge to load the retargeting-funnel skill from mbfinotti/advertising-skills.

Paste it into Claude, ChatGPT, Codex or Cursor.

Or read the skill source first.

Security evidence

Security state at 2026-09-30: reviewed. State definitions. This records static evidence for this revision; live load eligibility is checked again.

3 static scans, 0 counted findings. The listed scanners recorded the results shown for this package revision.

ScannerDateResultFindings
Edge static checks2026-09-27Pass0
Cisco skill-scanner2026-09-27Pass0
Semgrep Edge rules2026-09-27Pass0

Static scans check the code, not how well the skill works.

Scanner scope, raw findings and mirrored provider records

Edge static checks (Edge-run): edge-static/1.0.1. Scope: Static patterns for remote execution, credentials with network sends, obfuscation, prompt overrides, hidden Unicode, binaries and persistence. Revision: 7ede9c641c67d03fed5df54613f14e3d999a8716. Raw findings: . Counted findings: .

Cisco skill-scanner (Edge-run): cisco-skill-scanner/2.1.0. Scope: Local static, YARA, pipeline and behavioral analyzers; no LLM or AI Defense analysis. Revision: 7ede9c641c67d03fed5df54613f14e3d999a8716. Raw findings: . Counted findings: .

Semgrep Edge rules (Edge-run): semgrep/1.178.0+edge-rules.c15016a36fd3+offline-v1. Scope: Six Edge-authored static rules with Semgrep CE; offline execution and metrics disabled. Semgrep-maintained rules excluded. Revision: 7ede9c641c67d03fed5df54613f14e3d999a8716. Raw findings: . Counted findings: .

Source and licence

Repository
https://github.com/mbfinotti/advertising-skills
Pinned skill file
View source at revision
Revision
7ede9c641c67d03fed5df54613f14e3d999a8716
Package hash
sha256:68275fda9dda0873643c761494ec0e679899801cb34d2ee6b5054ca1dbb673ee
Licence
MIT