amazon-listing-grader

Score any Amazon product listing on a 0–100 scale across 7 dimensions. Returns a grade card with per-dimension scores and actionable improvement suggestions.

Requirements

CLAW_KEY env var set
CLAW_API_BASE env var (default: https://api.claw-school.com)
uv installed

Grade a listing

uv run ~/.openclaw/agents/sunny-xie/workspace/skills/amazon-listing-grader/scripts/grade.py <ASIN>

Example:

uv run ~/.openclaw/agents/sunny-xie/workspace/skills/amazon-listing-grader/scripts/grade.py B088FLY7S8

Scoring dimensions (100 pts total)

| Dimension | Max | Logic | |-----------|-----|-------| | Title length | 20 | 100–200 chars = 20; 50–100 or 200–250 = 12; else = 5 | | Bullet points | 20 | ≥5 = 20; 3–4 = 14; 1–2 = 7; 0 = 0 | | Star rating | 20 | ≥4.5 = 20; ≥4.0 = 14; ≥3.5 = 8; <3.5 = 3 | | Review count | 15 | ≥10K = 15; ≥1K = 12; ≥100 = 7; <100 = 3 | | Sales velocity | 15 | "bought in past month" present = 15; absent = 0 | | BSR | 10 | Any BSR present = 10; absent = 0 | | Badges | 10 | Amazon's Choice + Best Seller = 10; either = 7; none = 0 |

Grade scale

| Score | Grade | |-------|-------| | 85–100 | A — Excellent | | 70–84 | B — Good | | 55–69 | C — Average | | 40–54 | D — Needs Work | | 0–39 | F — Poor |

Output format

{
  "asin": "B088FLY7S8",
  "title": "12 Pack Small American Flags...",
  "total_score": 82,
  "grade": "B (Good)",
  "breakdown": {
    "title": 12,
    "bullets": 20,
    "rating": 20,
    "reviews": 7,
    "sales_velocity": 15,
    "bsr": 10,
    "badges": 10
  },
  "suggestions": [
    "Title is 45 chars — optimal is 100-200 chars"
  ]
}

Interpreting results

Present the results as a structured report. Call out:

Total score and grade label
Strongest dimensions (highest scores)
Weakest dimensions with the suggestions
Overall priority action (the suggestion that would give the biggest score boost)