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 brand-protection-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/brand-protection-walmart)<a href="https://agentmods.dev/skills/nexscope-ai/ecommerce-skills/brand-protection-walmart"><img src="https://agentmods.dev/badge/skills/nexscope-ai/ecommerce-skills/brand-protection-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/brand-protection-walmart"><img src="https://agentmods.dev/badge/skills/nexscope-ai/ecommerce-skills/brand-protection-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 16 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 | $0.00044 | $0.00725 |
| Opus 5 | $0.00022 | $0.00362 |
| Sonnet 5 | $0.00009 | $0.00145 |
| Haiku 4.5 | $0.00004 | $0.00072 |
Grade A, and why
brand-protection-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 13d 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 — 130 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Brand Protection — Walmart 🛡️
Protect your brand from unauthorized sellers and counterfeit products on Walmart Marketplace.
Installation
npx skills add nexscope-ai/eCommerce-Skills --skill brand-protection-walmart -g
Features
- Unauthorized Seller Detection — Find sellers without authorization
- Price Monitoring — MAP violation alerts
- Counterfeit Signals — Review-based fake detection
- Trademark Abuse — Listing title/description infringement
- Walmart Brand Portal — Official reporting templates
- WFS Monitoring — Track fulfillment-verified sellers
Walmart-Specific Detection
| Dimension | Method | Risk Level |
|---|---|---|
| Unauthorized Sellers | Seller ID monitoring | 🔴 High |
| Price Violations | Below MAP detection | 🔴 High |
| Counterfeit | Review keyword analysis | 🔴 High |
| Trademark | Title pattern matching | ⚠️ Medium |
Risk Levels
| Level | Description | Action |
|---|---|---|
| 🔴 High | Immediate threat | Report within 24h |
| ⚠️ Medium | Potential concern | Investigate further |
| ✅ Low | Normal activity | Continue monitoring |
Input Configuration
{
"brand_name": "YourBrand",
"trademark_number": "US12345678",
"brand_portal_enrolled": true,
"authorized_sellers": ["seller_id_1", "seller_id_2"],
"protected_item_ids": ["123456789"],
"min_price": 29.99
}
Usage
Detection
python3 scripts/detector.py
Generate Complaint Templates
# Walmart Brand Portal report
python3 scripts/templates.py brand-portal
# Cease & Desist letter
python3 scripts/templates.py cease-desist
# Test buy guide
python3 scripts/templates.py testbuy
Output Example
🛡️ Walmart Brand Protection Report
Brand: YourBrand
Items Monitored: 10
Analysis Date: 2024-01-15
━━━━━━━━━━━━━━━━━━━━━━━━
🔴 HIGH RISK ALERTS
Item: 123456789
├── 2 unauthorized sellers detected
├── Lowest price: $17.99 (MAP: $29.99)
└── Action: File Brand Portal complaint
━━━━━━━━━━━━━━━━━━━━━━━━
⚠️ COUNTERFEIT SIGNALS
Reviews mentioning "fake": 4
Reviews mentioning "not original": 1
Recommendation: Order test buy
What ships with it
2 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.
- 13d ago First seen · 130 lines · 44 tokens per session scan A a293a620e540
brand-protection-walmart is a skill published in the GitHub repository nexscope-ai/eCommerce-Skills (914 stars, last pushed 17d ago), licensed MIT. It adds 44 tokens to every session and 725 once invoked, about $0.0002 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 2026-08-30.
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