Purple Cow Audit

What the source does

• FilesystemNone observedNo reads or writes in the source
• NetworkNone observedNo outbound calls in the source
• ShellNone observedNo commands run in the source
• DependenciesPinnedNothing floats
• SecretsNone foundNo keys in source

Five audit layers

Gates applied: no behavioural pass.

Audit 0.4.1 · source sha 2515ce9634da · 15 Oct 2026Report an issue or request a re-scan

• PublisherAffitor GitHub organizationOwner of the repository this skill is read from
• Source folderAffitor/affiliate-skills/skills/research/purple-cow-auditThe exact folder we audited
• LicenceMITAs the repository states it
• Commit pinned for this verdict2515ce9634daA new audit runs when the source changes
• Repository statusNot archivedLast push 2 days ago
• Sandboxed runNot runSkills are read, not executed; layer L4 is skipped

Its description: Score product remarkability 1-10 to decide if it's worth promoting. Seth Godin's Purple Cow test. Triggers on: "is this product worth promoting", "should I promote", "product audit", "purple cow", "remarkable product",…

---
name: purple-cow-audit
description: >
  Score product remarkability 1-10 to decide if it's worth promoting. Seth Godin's Purple Cow test.
  Triggers on: "is this product worth promoting", "should I promote", "product audit",
  "purple cow", "remarkable product", "is it remarkable", "rate this product",
  "product quality check", "worth my reputation", "product evaluation",
  "would I recommend without commission", "product remarkability score",
  "evaluate this affiliate product", "quality gate for promotion".
license: MIT
version: "1.0.0"
tags: ["affiliate-marketing", "research", "niche-analysis", "program-discovery", "differentiation", "positioning"]
compatibility: "Claude Code, ChatGPT, Gemini CLI, Cursor, Windsurf, OpenClaw, any AI agent"
metadata:
  author: affitor
  version: "1.0"
  stage: S1-Research
---

# Purple Cow Audit

Quality gate for affiliate marketers: score a product's remarkability 1-10 before promoting it. Based on Seth Godin's Purple Cow — if the product isn't remarkable, no amount of marketing skill will make it convert sustainably. The key question: "Would I recommend this to a friend WITHOUT earning a commission?"

## Stage

S1: Research — Evaluating a program's worthiness IS part of research and discovery. This is a quality gate before you invest time creating content, landing pages, and email sequences.

## When to Use

- User is considering promoting a specific product
- User asks "is this product worth promoting?"
- User wants to evaluate product quality before investing time
- User says "purple cow", "remarkable", "audit", "evaluate", "quality check"
- Before investing time in S2-S5 skills for a specific product
- User has a list of programs from `affiliate-program-search` and needs to pick the best

## Input Schema

```yaml
product:                    # REQUIRED
  name: string              # Product name
  url: string               # Product website
  description: string       # OPTIONAL — what it does
  reward_value: string      # OPTIONAL — commission rate
  tags: string[]            # OPTIONAL — categories

comparison_products: string[] # OPTIONAL — competitors to compare against
                              # Default: auto-discovered
```

**Chaining from S1 affiliate-program-search**: If run, evaluate the `recommended_program`.

## Workflow

### Step 1: Research the Product

1. `web_search`: `"[product] review 2024 2025"` — find recent reviews
2. `web_search`: `"[product] vs" OR "[product] alternative"` — find competitors
3. `web_search`: `"[product] complaints" OR "[product] problems"` — find issues
4. Check product website for: pricing transparency, unique features, social proof

### Step 2: Score Remarkability

Rate each dimension 1-10:

| Dimension | Question | Weight |
|---|---|---|
| **Uniqueness** | Does it do something no competitor does? | 20% |
| **Quality** | Is it genuinely excellent at its core job? | 20% |
| **Story** | Does using it make you feel/look different? | 15% |
| **Word of mouth** | Would users tell friends unprompted? | 15% |
| **Design** | Is the experience delightful, not just functional? | 10% |
| **Problem fit** | Does it solve a real, painful problem? | 10% |
| **Trust** | Transparent pricing, good support, real social proof? | 10% |

**Composite score** = weighted average (1-10)

### Step 3: Make Recommendation

Based on composite score:
- **8-10: PROMOTE** — This is a Purple Cow. Go all in.
- **6-7: PROMOTE WITH ANGLE** — Good product, needs strong positioning. Identify your unique angle.
- **4-5: CAUTION** — Mediocre product. Only promote if commission is exceptional AND you can add significant value through bonuses.
- **1-3: SKIP** — Not remarkable. Promoting this will damage your reputation. Find an alternative.

### Step 4: Identify Remarkable Angles

For products scoring 6+, identify:
1. The 1-2 features that ARE remarkable (Purple Cow elements)
2. The angles that make it share-worthy
3. The audience segment for whom this IS a Purple Cow (even if not for everyone)

### Step 5: Self-Validation

- [ ] Score is evidence-based (cited reviews, features, data)
- [ ] Recommendation is honest (not inflated by high commission)
- [ ] Remarkable angles are specific (not generic praise)
- [ ] Comparison with competitors is fair
- [ ] The "would I recommend without commission" test was honestly applied

## Output Schema

```yaml
output_schema_version: "1.0.0"
purple_cow_audit:
  product_name: string
  composite_score: number       # 1-10 weighted
  recommendation: string        # "promote" | "promote_with_angle" | "caution" | "skip"
  scores:
    uniqueness: number
    quality: number
    story: number
    word_of_mouth: number
    design: number
    problem_fit: number
    trust: number

  remarkable_angles: string[]   # What makes it a Purple Cow (for 6+)
  red_flags: string[]           # Concerns identified
  alternative_products: string[] # Better options if score < 6

remarkability_score: number     # Alias for composite_score (for chaining)

chain_metadata:
  skill_slug: "purple-cow-audit"
  stage: "research"
  timestamp: string
  suggested_next:
    - "affiliate-program-search"
    - "grand-slam-offer"
    - "viral-post-writer"
    - "monopoly-niche-finder"
```

## Output Format

```
## Purple Cow Audit: [Product Name]

### The Question
Would I recommend [product] to a friend WITHOUT earning a commission?
**Answer:** [Yes/No/With caveats]

### Remarkability Scorecard

| Dimension | Score | Evidence |
|---|---|---|
| Uniqueness | X/10 | [specific evidence] |
| Quality | X/10 | [specific evidence] |
| Story | X/10 | [specific evidence] |
| Word of Mouth | X/10 | [specific evidence] |
| Design | X/10 | [specific evidence] |
| Problem Fit | X/10 | [specific evidence] |
| Trust | X/10 | [specific evidence] |
| **Composite** | **X/10** | |

### Recommendation: [PROMOTE / PROMOTE WITH ANGLE / CAUTION / SKIP]

[Reasoning — 2-3 sentences]

### Remarkable Angles (what to emphasize)
1. [Specific remarkable feature/aspect]
2. [Spe

Excerpt, first 6,000 characters of SKILL.md, verbatim from the audited commit. It is text from someone else’s repository, quoted so you can judge it before your agent reads it.

1. 2026-10-15
   ✓SAFE B 89 / 100

   first audit · source 2515ce9634da

Questions about Purple Cow Audit

• github.com/Affitor/affiliate-skills/tree/main/skills/research/pu — the audited source at commit 2515ce9634da and every finding aboveObserved · 15 Oct 2026

Spotted something wrong? Report a correction · Methodology