ecommerce-amazon-keyword-summary

ecommerce-amazon-keyword-summary is a skill for Claude Code from nexscope-ai/nexscope-ecommerce-skills. It costs 191 tokens per session (3,029 once invoked), scanned A, original, no licence file.

Keyword traffic analysis breaks down where competitor Amazon listings get visits, including unpaid search, sponsored ads, brand ads, video ads, recommendations, and newly discovered keywords.

In plain words
What is it for?
Use it to study competitor ASIN traffic sources, filter listings, choose date ranges, and find new keywords bringing visitors.
Why use it?
It shows which search and advertising routes bring traffic to competing products instead of treating all visits as the same.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the nexscope-ecommerce-skills plugin — 138 skills shipped together

Good fit Use it to study competitor ASIN traffic sources, filter listings, choose date ranges, and find new keywords bringing visitors.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/nexscope-ai/nexscope-ecommerce-skills/ecommerce-amazon-keyword-summary
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/nexscope-ecommerce-skills --skill ecommerce-amazon-keyword-summary
Clone the repo
git clone --depth 1 https://github.com/nexscope-ai/nexscope-ecommerce-skills

Made for: Claude Code.

Or install nexscope-ecommerce-skills, the plugin that ships this one along with the rest of its 138 skills.

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 ecommerce-amazon-keyword-summary

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

Your own site · 80×15
<a href="https://agentmods.dev/skills/nexscope-ai/nexscope-ecommerce-skills/ecommerce-amazon-keyword-summary"><img src="https://agentmods.dev/badge/skills/nexscope-ai/nexscope-ecommerce-skills/ecommerce-amazon-keyword-summary.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 191 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,029 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.
Origin unknown 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 $0.00191 $0.03029
Opus 5 $0.00096 $0.01515
Sonnet 5 $0.00038 $0.00606
Haiku 4.5 $0.00019 $0.00303

Measured 11d ago against content hash 5a70bacfed37, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

ecommerce-amazon-keyword-summary 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 11d ago.

The scan reads SKILL.md. This mod also ships 1 executable file (scripts/amazon_keyword_summary.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

ecommerce-amazon-keyword-summary/SKILL.md · 210 lines

The source is not reproduced here

No licence file

A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.

Read it on GitHub

Files

What ships with it

3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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. 11d ago First seen · 210 lines · 191 tokens per session scan A 5a70bacfed37

Subscribe to this mod's changes

ecommerce-amazon-keyword-summary is a skill published in the GitHub repository nexscope-ai/nexscope-ecommerce-skills (67 stars, last pushed 3d ago), with no licence file. It adds 191 tokens to every session and 3,029 once invoked, about $0.0010 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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