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 tiktok-shop-analyticsgit 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/tiktok-shop-analytics)<a href="https://agentmods.dev/skills/nexscope-ai/ecommerce-skills/tiktok-shop-analytics"><img src="https://agentmods.dev/badge/skills/nexscope-ai/ecommerce-skills/tiktok-shop-analytics/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/tiktok-shop-analytics"><img src="https://agentmods.dev/badge/skills/nexscope-ai/ecommerce-skills/tiktok-shop-analytics.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk pass
- 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 | $0.00053 | $0.01361 |
| Opus 5 | $0.00026 | $0.00681 |
| Sonnet 5 | $0.00011 | $0.00272 |
| Haiku 4.5 | $0.00005 | $0.00136 |
Grade A, and why
tiktok-shop-analytics 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 — 188 lines — stays where its author put it; the contents beside it link to each section on GitHub.
TikTok Shop Analytics 📊
Master data-driven selling on TikTok Shop. Track performance, optimize content, and scale what works.
Installation
npx skills add nexscope-ai/eCommerce-Skills --skill tiktok-shop-analytics -g
Usage Examples
Performance dashboard analysis:
"Analyze my TikTok Shop performance last month - which products and videos drove the most sales?"
Content optimization:
"My TikTok videos get views but low conversions - help me identify the problem"
Competitive benchmarking:
"How does my TikTok Shop performance compare to others in my category?"
Core Capabilities
1. Business Performance Analysis
- Revenue and sales trend tracking
- Customer acquisition and retention metrics
- Average order value (AOV) analysis
- Conversion funnel optimization
2. Content Performance Intelligence
- Video metrics analysis (views, engagement, shares)
- Content format performance comparison
- Hook effectiveness measurement
- Hashtag performance tracking
3. Live Selling Analytics
- Live stream performance metrics
- Audience engagement patterns
- Gross merchandise value (GMV) per live session
- Host performance evaluation
4. Creator & Affiliate Tracking
- Affiliate partner performance analysis
- Creator content ROI measurement
- Commission optimization insights
- Partnership scaling opportunities
How It Works
Step 1: Data Collection & Analysis
Comprehensive performance data gathering
Analyze key performance indicators:
- Extract sales data and revenue trends
- Review content performance metrics
- Evaluate customer behavior patterns
- Assess marketing channel effectiveness
Step 2: Performance Benchmarking
Competitive analysis and industry comparison
Compare against benchmarks:
- Industry average performance metrics
- Competitive content analysis
- Best-performing content identification
- Growth opportunity assessment
Step 3: Optimization Strategy Development
Data-driven improvement recommendations
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 · 188 lines · 53 tokens per session scan A c42a73ef40f9
tiktok-shop-analytics is a skill published in the GitHub repository nexscope-ai/eCommerce-Skills (914 stars, last pushed 17d ago), licensed MIT. It adds 53 tokens to every session and 1,361 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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