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-analysisgit 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-analysis)<a href="https://agentmods.dev/skills/nexscope-ai/amazon-skills/amazon-competitor-analysis"><img src="https://agentmods.dev/badge/skills/nexscope-ai/amazon-skills/amazon-competitor-analysis/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-analysis"><img src="https://agentmods.dev/badge/skills/nexscope-ai/amazon-skills/amazon-competitor-analysis.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk warn
- 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 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]
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 | $0.00065 | $0.01013 |
| Opus 5.5 | $0.00026 | $0.00405 |
| Sonnet 5.5 | $0.00013 | $0.00203 |
| Haiku 4.5 | $0.00006 | $0.00101 |
Grade A, and why
amazon-competitor-analysis 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 1mo 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 — 151 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Amazon Competitor Analysis 🏆
Full-spectrum competitor intelligence to outsmart your competition. Analyze listings, pricing, ads, and positioning gaps.
Installation
npx skills add nexscope-ai/Amazon-Skills --skill amazon-competitor-analysis -g
Usage Examples
Basic competitor analysis:
"Compare my dog bed against ASIN B0EXAMPLE1 and B0EXAMPLE2"
Competitive gap analysis:
"Find weaknesses in the top 5 competitors for 'wireless earbuds under $50'"
Market positioning analysis:
"How do competitors position their products in the home security category?"
Core Capabilities
1. Listing Quality Comparison
- Title optimization analysis vs competitors
- Bullet point effectiveness scoring
- Image quality and infographic comparison
- A+ Content analysis and gaps
2. Pricing & Positioning Strategy
- Price positioning in category context
- Deal frequency and promotional patterns
- Value proposition differentiation
- Market share estimation
3. Review Intelligence
- Sentiment comparison across competitors
- Common complaint patterns
- Feature request extraction
- Quality perception analysis
4. Advertising Visibility Assessment
- Sponsored placement frequency
- Keyword competition analysis
- Ad copy effectiveness review
- PPC spend estimation
How It Works
Step 1: Competitive Data Collection
Using web search and Amazon data sources
Search for competitor products and gather:
- Product listings and specifications
- Pricing history and current positions
- Review counts and sentiment patterns
- Advertising visibility signals
Step 2: Comparative Analysis
Multi-dimensional competitor comparison
Analyze key differentiation factors:
- Feature comparison matrix
- Price-value positioning
- Customer satisfaction gaps
- Market share indicators
Step 3: Strategic Recommendations
Actionable competitive intelligence
Generate specific recommendations:
- Pricing optimization opportunities
- Listing improvement priorities
- Product differentiation strategies
- Marketing positioning angles
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.
- 1mo ago First seen · 151 lines · 65 tokens per session scan A bea0b32f6032
amazon-competitor-analysis is a skill published in the GitHub repository nexscope-ai/Amazon-Skills (795 stars, last pushed 1mo ago), licensed MIT. It adds 65 tokens to every session and 1,013 once invoked, about $0.0003 per session on Opus 5.5. 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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