amazon-brand-analytics

amazon-brand-analytics is a skill for Claude Code, Codex from nexscope-ai/Amazon-Skills. It costs 131 tokens per session (2,006 once invoked), scanned A, original, MIT.

A guide for interpreting Amazon Brand Analytics, reports available to owners of Amazon Brand Registry accounts. It explains search rankings, shopping-basket relationships, product comparisons, customer groups, and seasonal patterns.

In plain words
What is it for?
Use it to analyze search data, find keyword or click-share gaps, plan bundles, compare products, study customer segments, or identify seasonal trends.
Why use it?
It turns the reports' metrics into findings about customer demand, competitors, cross-selling, and advertising opportunities.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: positional $N argument.

Good fit Use it to analyze search data, find keyword or click-share gaps, plan bundles, compare products, study customer segments, or identify seasonal trends.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/nexscope-ai/amazon-skills/amazon-brand-analytics
Install

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.

Any agent
npx skills add nexscope-ai/Amazon-Skills --skill amazon-brand-analytics
Clone the repo
git clone --depth 1 https://github.com/nexscope-ai/Amazon-Skills

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for amazon-brand-analytics

README.md
[![agentmods](https://agentmods.dev/badge/skills/nexscope-ai/amazon-skills/amazon-brand-analytics/github.svg)](https://agentmods.dev/skills/nexscope-ai/amazon-skills/amazon-brand-analytics)
Your own site
<a href="https://agentmods.dev/skills/nexscope-ai/amazon-skills/amazon-brand-analytics"><img src="https://agentmods.dev/badge/skills/nexscope-ai/amazon-skills/amazon-brand-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.

agentmods 80×15 button for amazon-brand-analytics

Your own site · 80×15
<a href="https://agentmods.dev/skills/nexscope-ai/amazon-skills/amazon-brand-analytics"><img src="https://agentmods.dev/badge/skills/nexscope-ai/amazon-skills/amazon-brand-analytics.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 131 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,006 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • Socket pass 27 May 2026
  • Snyk warn 27 May 2026
  • NVIDIA SkillSpector warn 7 Sept 2026
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 198
    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 212
    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]
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00131 $0.02006
Opus 5 $0.00066 $0.01003
Sonnet 5 $0.00026 $0.00401
Haiku 4.5 $0.00013 $0.00201

Measured 9d ago against content hash 5cf1a942f210, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

amazon-brand-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.

amazon-brand-analytics/SKILL.md · 233 lines

How it starts

The opening of the file, as written. The whole thing — 233 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Amazon Brand Analytics 📊

Unlock Brand Analytics insights for strategic growth. Requires Brand Registry — works with your data.

Installation

npx skills add nexscope-ai/Amazon-Skills --skill amazon-brand-analytics -g

Capabilities

  • Search Frequency Rank (SFR) analysis: Decode keyword opportunities, click share gaps, and conversion optimization
  • Market Basket intelligence: Identify cross-sell opportunities, bundle strategies, and category expansion
  • Item Comparison insights: Understand competitive positioning and customer consideration factors
  • Demographic analysis: Extract customer segment insights and geographic opportunities
  • Seasonal trend detection: Identify timing patterns and market shifts from search data
  • Strategic recommendations: Convert raw data into actionable growth strategies
  • Multi-marketplace support: Works with Brand Analytics from all Amazon regions

Usage Examples

Users can ask naturally. Examples:

Analyze my Search Frequency Rank data for "wireless earbuds" — show keyword opportunities and click share gaps
Review my Market Basket data for the last 6 months. What cross-sell and bundling opportunities do you see?
Interpret my Item Comparison report for yoga mats — how do customers evaluate my product vs competitors?
Generate Brand Analytics strategy report for Q4 combining SFR, Market Basket, and demographic data
Find seasonal trends and opportunity keywords from my Brand Analytics data for kitchen appliances

Three Analysis Modes

Mode Input Required Output Best For
SFR Analysis Search Frequency Rank data export Keyword opportunities, click/conversion gaps Advertising optimization
Market Basket Market Basket Analysis export Cross-sell opportunities, bundle recommendations Product strategy
Item Comparison Item Comparison report data Competitive positioning insights Product development

Read the full file on GitHub · 233 lines

Changes

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.

  1. 9d ago First seen · 233 lines · 131 tokens per session scan A 5cf1a942f210

Subscribe to this mod's changes

amazon-brand-analytics is a skill published in the GitHub repository nexscope-ai/Amazon-Skills (644 stars, last pushed 14d ago), licensed MIT. It adds 131 tokens to every session and 2,006 once invoked, about $0.0007 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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