Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add nexscope-ai/eCommerce-Skills --skill supply-chain-optimization-walmartgit clone --depth 1 https://github.com/nexscope-ai/eCommerce-SkillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/nexscope-ai/ecommerce-skills/supply-chain-optimization-walmart)<a href="https://agentmods.dev/skills/nexscope-ai/ecommerce-skills/supply-chain-optimization-walmart"><img src="https://agentmods.dev/badge/skills/nexscope-ai/ecommerce-skills/supply-chain-optimization-walmart/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/nexscope-ai/ecommerce-skills/supply-chain-optimization-walmart"><img src="https://agentmods.dev/badge/skills/nexscope-ai/ecommerce-skills/supply-chain-optimization-walmart.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium MCP Rug Pull · line 15 npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.Fix: Pin the version: npx @scope/[email protected]
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00059 | $0.00888 |
| Opus 5 | $0.00030 | $0.00444 |
| Sonnet 5 | $0.00012 | $0.00178 |
| Haiku 4.5 | $0.00006 | $0.00089 |
Grade A, and why
supply-chain-optimization-walmart scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 137 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Supply Chain Optimization — Walmart 📦
Supply chain bottleneck analyzer for Walmart Marketplace sellers. Diagnose cash flow, inventory, WFS costs, and referral fees.
Installation
npx skills add nexscope-ai/eCommerce-Skills --skill supply-chain-optimization-walmart -g
Platform Characteristics
| Feature | Walmart | vs Amazon |
|---|---|---|
| Fulfillment | WFS (Walmart Fulfillment Services) | FBA |
| Commission | 6-15% (by category) | 8-15% |
| Payment cycle | 14-21 days | 14 days |
| Storage fees | Lower | Higher |
| Long-term storage | No extra fee | Yes |
Cost Structure (Walmart)
Selling Price $XX
├── Product Cost
├── Inbound Shipping
├── WFS Fulfillment Fee (similar to FBA)
├── WFS Storage Fee (lower than FBA)
├── Referral Fee (6-15%)
├── Advertising (Walmart Connect)
└── Net Profit
Benchmark Configuration
BENCHMARKS = {
"walmart": {
"gross_margin": {
"healthy": 0.35, # Walmart commission lower, benchmark can be lower
"warning": 0.25,
"danger": 0.15
},
"shipping_ratio": {
"healthy": 0.06, # WFS shipping slightly higher
"warning": 0.10,
"danger": 0.15
},
"inventory_days": {
"healthy": 45,
"warning": 60,
"danger": 90
},
"cash_cycle": {
"healthy": 100, # Payment cycle slightly longer
"warning": 130,
"danger": 160
},
"net_margin": {
"healthy": 0.18,
"warning": 0.10,
"danger": 0.05
}
}
}
API Integration
Walmart Marketplace API
export WALMART_CLIENT_ID="xxx"
export WALMART_CLIENT_SECRET="xxx"
Available Data
| Data | API |
|---|---|
| Orders | Orders API |
| Inventory | Inventory API |
| Fee Reports | Reports API |
Usage Flow
Same 4-step process as Amazon version:
- Business profile collection
- Supply chain data collection
- Bottleneck diagnosis
- Cost reduction plan output
What ships with it
3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 9d ago First seen · 137 lines · 59 tokens per session scan A 637c02dfbb54
supply-chain-optimization-walmart is a skill published in the GitHub repository nexscope-ai/eCommerce-Skills (914 stars, last pushed 17d ago), licensed MIT. It adds 59 tokens to every session and 888 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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