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/Amazon-Skills --skill amazon-competitor-monitoringgit clone --depth 1 https://github.com/nexscope-ai/Amazon-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/amazon-skills/amazon-competitor-monitoring)<a href="https://agentmods.dev/skills/nexscope-ai/amazon-skills/amazon-competitor-monitoring"><img src="https://agentmods.dev/badge/skills/nexscope-ai/amazon-skills/amazon-competitor-monitoring/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/amazon-skills/amazon-competitor-monitoring"><img src="https://agentmods.dev/badge/skills/nexscope-ai/amazon-skills/amazon-competitor-monitoring.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk warn
- NVIDIA SkillSpector warn
SkillSpector: 3 findings, 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 14 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]
- medium MCP Rug Pull · line 143 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]
- medium MCP Rug Pull · line 157 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 | $0.00128 | $0.01552 |
| Opus 5 | $0.00064 | $0.00776 |
| Sonnet 5 | $0.00026 | $0.00310 |
| Haiku 4.5 | $0.00013 | $0.00155 |
Grade A, and why
amazon-competitor-monitoring 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 12d 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 — 174 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Amazon Competitor Monitoring 🔍
Track competitor strategies, pricing changes, and market opportunities. No API key — works out of the box.
Installation
npx skills add nexscope-ai/Amazon-Skills --skill amazon-competitor-monitoring -g
Capabilities
- Price monitoring: Track competitor pricing changes, discount patterns, and Buy Box rotation
- Inventory tracking: Monitor stock levels, restock patterns, and out-of-stock opportunities
- Product launches: Detect new competitor products and category expansions
- Review intelligence: Analyze review velocity, rating changes, and sentiment shifts
- Advertising insights: Identify competitor ad strategies and keyword targeting patterns
- Performance benchmarking: Compare your metrics against competitor baselines
- Multi-marketplace support: US, UK, DE, FR, IT, ES, JP, CA, AU, IN, MX, BR
Usage Examples
Users can ask naturally. Examples:
Monitor competitor ASIN B08XYZ123 for pricing changes on Amazon US
Track the top 5 competitors in portable blenders category — alert me for price drops over 10%
Analyze competitor pricing strategy for ASIN B09ABC456 over the last 90 days
Set up monitoring for yoga mat category — track new launches and inventory patterns
Compare my product B0DEF789 against top 3 competitors: pricing, reviews, and BSR performance
Workflow
Step 1: Identify Competitors
Use web_search to find competitor products:
- Search
"[product category]" site:amazon.com— identify top products by relevance - Search
"[your main keyword]" amazon best sellers— find category leaders - Extract ASINs, current prices, ratings, and BSR data from search results
Step 2: Baseline Data Collection
For each competitor ASIN, use web_fetch to gather current state:
- Product title and current price
- Best Seller Rank and category position
- Customer rating and review count
- Availability status (in stock/low stock/out of stock)
- Prime eligibility and shipping options
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.
- 12d ago First seen · 174 lines · 128 tokens per session scan A b08688bc341e
amazon-competitor-monitoring is a skill published in the GitHub repository nexscope-ai/Amazon-Skills (661 stars, last pushed 17d ago), licensed MIT. It adds 128 tokens to every session and 1,552 once invoked, about $0.0006 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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