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 social-media-monitorgit 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/social-media-monitor)<a href="https://agentmods.dev/skills/nexscope-ai/ecommerce-skills/social-media-monitor"><img src="https://agentmods.dev/badge/skills/nexscope-ai/ecommerce-skills/social-media-monitor/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/social-media-monitor"><img src="https://agentmods.dev/badge/skills/nexscope-ai/ecommerce-skills/social-media-monitor.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 21 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 | $0.00038 | $0.00526 |
| Opus 5 | $0.00019 | $0.00263 |
| Sonnet 5 | $0.00008 | $0.00105 |
| Haiku 4.5 | $0.00004 | $0.00053 |
Grade A, and why
social-media-monitor 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 — 65 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Social Media Monitor 📱
Monitor social media mentions, trends, and competitor activity for e-commerce brands. Set up listening workflows across Reddit, TikTok, Instagram, Twitter/X, and YouTube.
Supported platforms: Amazon, Shopify, WooCommerce, Walmart, TikTok Shop, Etsy, eBay, BigCommerce.
Built by Nexscope — your AI assistant for smarter e-commerce decisions.
Install
npx skills add nexscope-ai/eCommerce-Skills --skill social-media-monitor -g
Usage
Set up social media monitoring for my skincare brand. I want to track mentions on TikTok, Instagram, and Reddit. Also monitor 3 competitors.
Capabilities
- Social listening keyword and hashtag setup
- Platform-specific monitoring strategy (Reddit, TikTok, Instagram, Twitter, YouTube)
- Sentiment tracking methodology
- Competitor social media activity tracking
- Influencer mention detection
- Crisis detection and response framework
- UGC (user-generated content) discovery for marketing
How This Skill Works
Step 1: Collect information from the user's message — product, platform, current situation, and goals.
Step 2: Ask one follow-up with all remaining questions using multiple-choice format. Allow shorthand answers (e.g., "1b 2c 3a").
Step 3: Research and analyze using the frameworks and methodology below.
Step 4: Deliver structured, actionable output with specific recommendations, not vague advice.
Output Format
- Start with a summary of findings
- Include specific data points and benchmarks where available
- Provide prioritized action items
- Mark estimates with ⚠️ when based on incomplete data
- End with concrete next steps
Other Skills
More e-commerce skills: nexscope-ai/eCommerce-Skills
Amazon-specific skills: nexscope-ai/Amazon-Skills
Built by Nexscope — your AI assistant for smarter e-commerce decisions.
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 · 65 lines · 38 tokens per session scan A 3a1a17bcc4b1
social-media-monitor is a skill published in the GitHub repository nexscope-ai/eCommerce-Skills (914 stars, last pushed 17d ago), licensed MIT. It adds 38 tokens to every session and 526 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 2026-09-03.
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