← Back to Skills Marketplace
nexscope

Amazon Brand Analytics

by nexscope-ai · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ⚠ suspicious
119
Downloads
0
Stars
0
Active Installs
1
Versions
Install in OpenClaw
/install amazon-brand-analytics-skill
Description
Interpret and act on Amazon Brand Analytics data. Analyze Search Frequency Rank (SFR), click share, conversion share, market basket analysis, and repeat purc...
README (SKILL.md)

Amazon Brand Analytics 📋

Interpret and act on Amazon Brand Analytics data. Analyze Search Frequency Rank (SFR), click share, conversion share, market basket analysis, and repeat purchase behavior to optimize your Amazon strategy.

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 amazon-brand-analytics -g

Usage

Help me analyze my Amazon Brand Analytics data. My top search term has SFR #5,200 with 15% click share but only 8% conversion share. What should I do?

Capabilities

  • Search Frequency Rank (SFR) trend interpretation
  • Click share and conversion share analysis
  • Market basket analysis (frequently bought together insights)
  • Repeat purchase behavior patterns
  • Demographics data interpretation
  • Search term performance optimization recommendations

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.

Usage Guidance
This skill appears to be a conversational/consulting helper that expects you to provide Amazon Brand Analytics data rather than fetch it automatically. Before installing or running the suggested `npx` command: 1) Understand that the registry entry contains no code — the SKILL.md's install line points at an external package you would be pulling from npm/GitHub; verify that repository and package before running it. 2) If you expect automatic integration with Amazon, Shopify, etc., ask the author how credentials are handled — the skill currently declares no credential requirements, so it likely cannot fetch data without additional setup. 3) Do not paste sensitive credentials or tokens into chat; provide only the data you want analyzed or authorize integrations via vetted connectors. 4) If you decide to install the external package, review its source code and publisher identity (nexscope-ai) and prefer installing from the official GitHub repository or an audited package. The main risks here are supply-chain (running an external installer referenced only in SKILL.md) and mistaken expectations about automatic platform integrations.
Capability Analysis
Type: OpenClaw Skill Name: amazon-brand-analytics-skill Version: 1.0.0 The skill bundle consists of metadata and markdown instructions (SKILL.md) designed to guide an AI agent in analyzing Amazon Brand Analytics data. There is no executable code, no evidence of data exfiltration, and no malicious prompt injection. The instructions are entirely consistent with the stated purpose of providing e-commerce strategy recommendations.
Capability Assessment
ℹ Purpose & Capability
The skill's stated purpose (analyzing Amazon Brand Analytics metrics) aligns with an advisory/consulting skill that works from user-provided data. However the SKILL.md also claims support for many e-commerce platforms (Shopify, WooCommerce, Walmart, etc.) while the manifest requests no credentials or integration configuration — a mismatch that suggests the skill won't actually connect to those platforms itself and likely expects users to paste data. Additionally, the SKILL.md includes an `npx skills add ...` install command referencing an external package, but the registry entry contains no install spec or code files.
ℹ Instruction Scope
The runtime instructions are high-level: collect info from the user's message, ask one follow-up, research and analyze, then produce recommendations. They do not instruct the agent to read local files, environment variables, or external credentials. The instructions are vague about what 'research' entails (no explicit allowed endpoints or data sources), which gives the agent broad discretion but is consistent with a purely advisory skill.
⚠ Install Mechanism
There is no formal install spec in the manifest, but SKILL.md suggests installing an external package via `npx skills add nexscope-ai/eCommerce-Skills --skill amazon-brand-analytics -g`. That creates a disconnect: the package referenced may install code from npm/GitHub, yet this registry entry is instruction-only. Users following that install line would be executing an external installer not represented in this skill bundle. This is an incoherence and a potential supply-chain risk if you follow the published install step without verifying the external package.
ℹ Credentials
The skill declares no required environment variables, credentials, or config paths. For an advisory tool that expects the user to paste or describe Brand Analytics data this is proportional. If a user expects the skill to fetch Amazon or other platform data automatically, the lack of credential requirements is a mismatch and the skill will not be able to do that without additional setup.
✓ Persistence & Privilege
No persistent or privileged settings are requested (always is false, no install spec in the manifest). The skill does not request to be always-enabled and there is no indication it modifies other skills or system configuration.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install amazon-brand-analytics-skill
  3. After installation, invoke the skill by name or use /amazon-brand-analytics-skill
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
- Initial release of the Amazon Brand Analytics skill by Nexscope. - Analyze and interpret Amazon Brand Analytics data for smarter e-commerce decisions. - Supports key insights: Search Frequency Rank trends, click share vs conversion share, market basket analysis, repeat purchase behavior, and demographics. - Guidance and recommendations are structured with summaries, benchmarks, action items, and next steps. - Supports additional platforms including Shopify, Walmart, TikTok Shop, Etsy, eBay, WooCommerce, and BigCommerce.
Metadata
Slug amazon-brand-analytics-skill
Version 1.0.0
License MIT-0
All-time Installs 0
Active Installs 0
Total Versions 1
Frequently Asked Questions

What is Amazon Brand Analytics?

Interpret and act on Amazon Brand Analytics data. Analyze Search Frequency Rank (SFR), click share, conversion share, market basket analysis, and repeat purc... It is an AI Agent Skill for Claude Code / OpenClaw, with 119 downloads so far.

How do I install Amazon Brand Analytics?

Run "/install amazon-brand-analytics-skill" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is Amazon Brand Analytics free?

Yes, Amazon Brand Analytics is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does Amazon Brand Analytics support?

Amazon Brand Analytics is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Amazon Brand Analytics?

It is built and maintained by nexscope-ai (@nexscope); the current version is v1.0.0.

More Skills
self-improving agent
Captures learnings, errors, and corrections to enable continuous improvement. Use when: (1) A command or operation fails unexpectedly, (2) User corrects Clau...
⬇ 463283 · by pskoett
Skill Vetter
Security-first skill vetting for AI agents. Use before installing any skill from ClawdHub, GitHub, or other sources. Checks for red flags, permission scope, and suspicious patterns.
⬇ 259410 · by spclaudehome
Polymarket
Query Polymarket prediction markets. Check odds, find trending markets, search events, track price movements.
⬇ 232503 · by joelchance
Self-Improving + Proactive Agent
Self-reflection + Self-criticism + Self-learning + Self-organizing memory. Agent evaluates its own work, catches mistakes, and improves permanently. Use when...
⬇ 200423 · by ivangdavila
Github
Interact with GitHub using the `gh` CLI. Use `gh issue`, `gh pr`, `gh run`, and `gh api` for issues, PRs, CI runs, and advanced queries.
⬇ 191115 · by steipete
ontology
Typed knowledge graph for structured agent memory and composable skills. Use when creating/querying entities (Person, Project, Task, Event, Document), linkin...
⬇ 190156 · by oswalpalash

💬 Comments