Agent skill · Audited from source

Supply Chain Optimization Amazon

skill · nexscope-ai/eCommerce-SkillsMIT licenceAudited 19 Oct 2026 · source 3e6c611584c3

★ 1,192pushed 54 days agoversion 1.0.0
✓SAFEGrade B · 89/100 · 19 Oct 2026 · 3e6c611
1,192repo stars · whole nexscope-ai/eCommerce-Skills

Is it safe? Yes — SAFE, grade B (89/100). We read this skill's source at commit 3e6c611584c3 and found no filesystem, network or shell access and no hard-coded secrets. What it does: Supply Chain Optimization (Lite) - Diagnose bottlenecks and provide cost reduction strategies through conversation

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Cite this page

ModelsAtlas. “Supply Chain Optimization Amazon (nexscope-ai/eCommerce-Skills)”. Retrieved 19 Oct 2026. https://modelsatlas.com/skills/nexscope-ai/supply-chain-optimization-amazon

Trust audit

Audit 0.4.1 · source read 19 Oct 2026

Trust score89/100✓SAFE B
0 critical0 high0 medium0 low0 info

SAFE means nothing in the source contradicts what the skill says it does. Grade B is shared by 13,985 of 14,816 audited skills.

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

LayerWhat we checkResultFindings
L0 ProvenanceRepo owner, licence, archive status, activityPASS0
L1 Static sourceSecrets, path traversal, supply chain, hidden codePASS0
L2 InstructionsPrompt injection, authority framing, hidden directivesPASS0
L3 InventoryThe files and declarations match the sourcePASS0
L4 SandboxRun in isolation and watch behaviourSKIPPED why0

Gates applied: no behavioural pass.

Findings (0)

No findings at any severity. We re-audit when the source changes.

Audit 0.4.1 · source sha 3e6c611584c3 · 19 Oct 2026Report an issue or request a re-scan

Provenance

Who published it, and what the verdict is pinned to

  • Publishernexscope-ai GitHub organizationOwner of the repository this skill is read from
  • Source foldernexscope-ai/eCommerce-Skills/supply-chain-optimization/supply-chain-optimization-amazonThe exact folder we audited
  • LicenceMITAs the repository states it
  • Commit pinned for this verdict3e6c611584c3A new audit runs when the source changes
  • Repository statusNot archivedLast push 54 days ago
  • Sandboxed runNot runSkills are read, not executed; layer L4 is skipped

What it tells the agent

Full source on GitHub ↗

Its description: Supply Chain Optimization (Lite) - Diagnose bottlenecks and provide cost reduction strategies through conversation

---
name: supply-chain-optimization-amazon-lite
version: 1.0.0
description: Supply Chain Optimization (Lite) - Diagnose bottlenecks and provide cost reduction strategies through conversation
platform: amazon
lang: en
---

# Supply Chain Optimization (Lite)

Supply chain bottleneck analysis tool - Conversation-based version

No API integration required. Collect data through guided conversation, automatically diagnose bottlenecks and output cost reduction strategies.

## Use Cases

- Amazon seller supply chain health check
- Bottleneck identification and cost optimization
- Supply chain decision support

## Workflow

### Step 1: Trigger Skill

User says:
```
Analyze my supply chain
Supply chain diagnosis
I want to optimize supply chain costs
```

### Step 2: Business Profile Collection

Guide user to describe in natural language:

```
👋 Starting Supply Chain Analysis

Please describe your situation in a sentence or two, like:
"I sell kitchen products, 15 SKUs, $50K monthly sales, sourcing from Yiwu, sea freight to FBA, shipping costs seem high"

Or just tell me what problem you want to solve.
```

**Identify and confirm:**
- Category
- SKU count
- Monthly revenue scale
- Sourcing location
- Logistics model
- Main pain points

### Step 3: Supply Chain Data Collection

Guide user to provide key data:

```
📊 I need some data to locate bottlenecks (rough numbers are fine)

**Sourcing**
• Product cost (FOB): $___/unit
• Supplier payment terms: ___ days
• Lead time: ___ days

**Logistics**
• Shipping cost per unit: $___
• Transit time: ___ days

**Sales**
• Average selling price: $___
• FBA fulfillment fee: $___/unit
• Monthly storage fee: $___/unit
• Ad spend ratio: ___%

**Inventory**
• Current inventory days: ___ days
• Long-term storage fees: Yes/No

Just reply in natural language.
```

### Step 4: Bottleneck Diagnosis

Run calculation script:

```bash
python3 scripts/calculator.py '{"product_cost": 8, "supplier_payment_days": 0, ...}'
```

Output diagnosis report:
- Key metrics table (with health status)
- Cost structure breakdown
- Top 3 bottlenecks

### Step 5: Cost Reduction Strategies

For each bottleneck provide:
- Problem description
- Impact analysis
- Specific recommendations
- Action checklist

### Step 6: Output Format Selection

```
📤 Analysis complete! Choose output format:

1️⃣ **Text** - View in current conversation (already shown)
2️⃣ **Web Chart** - Generate visual report webpage
3️⃣ **Report Doc** - Document format for sharing/presentation

Reply with number or say "generate web report"
```

---

## Benchmark Configuration

The following benchmarks can be customized based on your business:

| Metric | Healthy | Warning | Danger |
|--------|---------|---------|--------|
| Gross Margin | >40% | 30-40% | <30% |
| Shipping Ratio | <5% | 5-10% | >10% |
| Net Margin | >20% | 10-20% | <10% |
| Inventory Turnover | <45 days | 45-60 days | >60 days |
| Cash Cycle | <90 days | 90-120 days | >120 days |

To adjust, modify `BENCHMARKS` in `scripts/calculator.py`.

---

## File Structure

```
amazon-lite/
├── SKILL.md          # Index (this file)
├── SKILL.en.md       # English version
├── SKILL.zh-CN.md    # Chinese version
├── _meta.json
└── scripts/
    └── calculator.py
```

---

_Version 1.0.0 | Platform: Amazon | Lang: English_

---

**Part of [Nexscope AI](https://www.nexscope.ai/?co-from=skill) — AI tools for e-commerce sellers.**

Excerpt, first 3,404 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.

Install

Pinned to the audited commit 3e6c611

Download folder ↗
git clone https://github.com/nexscope-ai/eCommerce-Skills
git -C eCommerce-Skills checkout 3e6c611584c3

The author documents no install command, so this uses the repository directly. Our verdict covers commit 3e6c611584c3 only.

Works in

The author has not said which agents this skill supports, and we have not tested it in any.

Audit history

Every audit, every source change

  1. ✓SAFE B 89 / 100

    first audit · source 3e6c611584c3

README badge

For maintainers · shows the latest audit

ModelsAtlas: SAFE BMODELSATLASSAFE · B
[![ModelsAtlas: SAFE B](https://modelsatlas.com/skills/nexscope-ai/supply-chain-optimization-amazon/badge.svg)](https://modelsatlas.com/skills/nexscope-ai/supply-chain-optimization-amazon/)

The badge shows our verdict and grade for this skill, and links back to this page. It changes when the audit does.

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Add this badge to your README

[![ModelsAtlas: SAFE B](https://modelsatlas.com/skills/nexscope-ai/supply-chain-optimization-amazon/badge.svg)](https://modelsatlas.com/skills/nexscope-ai/supply-chain-optimization-amazon/)

Questions about Supply Chain Optimization Amazon

What does the Supply Chain Optimization Amazon skill do?
E-commerce skills for AI agents — product research, marketing automation, supply chain optimization, and business analytics for online sellers across Amazon, Shopify, Etsy, TikTok Shop, and all platforms.
Is Supply Chain Optimization Amazon safe to install?
The audit found nothing in the source that contradicts what it says it does, and graded it B (89/100). Grade A is held back for packages that have also passed a sandboxed behavioural run, which is why a clean skill reads B.
What can Supply Chain Optimization Amazon access on my machine?
The audit observed no filesystem, network or shell use at all in its source.
How current is this page?
The grade is for one exact copy of the source (3e6c611584c3), read on 2026-10-19. The repository is watched, and a new audit runs when it changes — this is the first audit.

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