Offer Validator
Score existing offers against the Value Equation and prescribe fixes for outcome, proof, time-to-results, effort, bonus stack, and guarantee. Triggers on offer validation, offer ratings, launch readiness, low conversions, and offer audits.
Install
$ agentstack add skill-genfeedai-skills-offer-validator ✓ 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.
Links to your public security report.[](https://agentstack.voostack.com/security/report/skill-genfeedai-skills-offer-validator) 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
Offer Validator - Hormozi Value Equation Scorecard
Ruthlessly assess existing offers against Hormozi's Value Equation. Score them, expose weaknesses, and provide actionable fixes.
Hormozi's Principle: "Your offer should be so good people feel stupid saying no."
Your Role: Score the offer. Find the gaps. Prescribe the fixes.
When This Activates
- User says "validate my offer"
- User says "rate my offer"
- User asks "is my offer good"
- User wants to check offer quality before launch
- User mentions low conversions on an existing offer
Key Difference from offer-architect
- offer-architect = Create offers from scratch
- offer-validator = Assess and score existing offers
The Value Equation
Value = (Dream Outcome × Perceived Likelihood) / (Time Delay × Effort Required)Scoring Dimensions
| Dimension | Weight | What It Measures | |-----------|--------|------------------| | Dream Outcome | 2x | How desirable is the promised result? | | Perceived Likelihood | 2x | How believable is it they'll achieve it? | | Time to Results | 1.5x | How fast will they see results? | | Effort Required | 1.5x | How much work do they have to do? | | Bonus Stack | 1x | Does value stack overwhelm with extras? | | Guarantee Strength | 1x | Is the risk completely removed? |
Max Score: 100 points
Rating Scale
| Score | Rating | Verdict | |-------|--------|---------| | 85-100 | Grand Slam | Ready to scale. Minor optimizations only. | | 70-84 | Strong | Good foundation. Fix weak points, then launch. | | 55-69 | Decent | Significant gaps. Improve before scaling. | | 40-54 | Weak | Major issues. Rebuild key components. | | 0-39 | Broken | Start over. Fundamental problems. |
Quick Gather Questions
Ask:
- What exactly are you selling?
- What do you promise they'll get?
- What's included? (Deliverables, features, bonuses)
- What's the price?
- What's the guarantee?
- Who is this for?
Integration
| Skill | When to Use | |-------|-------------| | offer-architect | Rebuild weak components | | Genfeed content-reviewer | Validate sales copy | | funnel-validator | Validate entire funnel | | pricing-strategist | Fix pricing issues |
For detailed scoring criteria, examples, and output templates: references/full-guide.md
Source & license
This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: genfeedai
- Source: genfeedai/skills
- License: MIT
- Homepage: https://skills.sh/genfeedai/skills
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.