cac-roas-benchmark

Compute a business's CAC and ROAS family metrics from real spend and outcome data.

What this skill does for you

Compute a business's CAC and ROAS family metrics from real spend and outcome data, then judge whether the spend is healthy against three references - the business's own break-even, its own trailing history, and provenance-labelled external benchmarks - returning healthy, watch, unhealthy, or insufficient evidence. Use whenever the user asks whether their CAC is too high, whether a ROAS is good, what ROAS to aim for, whether ads are profitable, or mentions MER, blended CAC, payback period, or a spend health check - even if they never say 'benchmark'. Covers B2B/SaaS (cost per SQL, cost per closed-won, cohort lag) and B2C/ecommerce. Do NOT use to set those thresholds as policy - use mbfinotti/advertising-skills@ad-spend-guardrails instead.

Quoted from the skill description in the pinned source

Who made it

Publishermbfinotti

Repositoryadvertising-skills

Installs831as 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 cac-roas-benchmark 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.

Scanner	Date	Result
Edge static checks	2026-09-27	Pass
Cisco skill-scanner	2026-09-27	Pass
Semgrep Edge rules	2026-09-27	Pass

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: sha256:234cf5c75a017a07c87b2c8eddd2baf527d6043401d1b35c700d9e841e221ac9
Licence: MIT