Agent skill · Audited from source

Amazon Negative Keywords

skill · nexscope-ai/Amazon-SkillsMIT licenceAudited 19 Oct 2026 · source 1bc9142374b1

★ 783pushed 54 days ago
✓SAFEGrade B · 89/100 · 19 Oct 2026 · 1bc9142
783repo stars · whole nexscope-ai/Amazon-Skills

Is it safe? Yes — SAFE, grade B (89/100). We read this skill's source at commit 1bc9142374b1 and found no filesystem, network or shell access and no hard-coded secrets. What it does: Amazon negative keyword management and optimization. Search term analysis, waste reduction, savings estimation, and automated negative keyword strategies. Use when the user asks about negative keywords, search term…

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ModelsAtlas. “Amazon Negative Keywords (nexscope-ai/Amazon-Skills)”. Retrieved 19 Oct 2026. https://modelsatlas.com/skills/nexscope-ai/amazon-negative-keywords

Trust audit

Audit 0.4.1 · source read 19 Oct 2026

Trust score89/100✓SAFE B
0 critical0 high0 medium0 low0 info

SAFE means nothing in the source contradicts what the skill says it does. Grade B is shared by 13,985 of 14,816 audited skills.

What the source does

  • FilesystemNone observedNo reads or writes in the source
  • NetworkNone observedNo outbound calls in the source
  • ShellNone observedNo commands run in the source
  • DependenciesPinnedNothing floats
  • SecretsNone foundNo keys in source

Five audit layers

LayerWhat we checkResultFindings
L0 ProvenanceRepo owner, licence, archive status, activityPASS0
L1 Static sourceSecrets, path traversal, supply chain, hidden codeNA0
L2 InstructionsPrompt injection, authority framing, hidden directivesPASS0
L3 InventoryThe files and declarations match the sourcePASS0
L4 SandboxRun in isolation and watch behaviourSKIPPED why0

Gates applied: no behavioural pass.

Findings (0)

No findings at any severity. We re-audit when the source changes.

Audit 0.4.1 · source sha 1bc9142374b1 · 19 Oct 2026Report an issue or request a re-scan

Provenance

Who published it, and what the verdict is pinned to

  • Publishernexscope-ai GitHub organizationOwner of the repository this skill is read from
  • Source foldernexscope-ai/Amazon-Skills/amazon-negative-keywordsThe exact folder we audited
  • LicenceMITAs the repository states it
  • Commit pinned for this verdict1bc9142374b1A new audit runs when the source changes
  • Repository statusNot archivedLast push 54 days ago
  • Sandboxed runNot runSkills are read, not executed; layer L4 is skipped

What it tells the agent

Full source on GitHub ↗

Its description: Amazon negative keyword management and optimization. Search term analysis, waste reduction, savings estimation, and automated negative keyword strategies. Use when the user asks about negative keywords, search term…

---
name: amazon-negative-keywords
description: "Amazon negative keyword management and optimization. Search term analysis, waste reduction, savings estimation, and automated negative keyword strategies. Use when the user asks about negative keywords, search term analysis, ad waste reduction, or PPC optimization."
metadata: {"nexscope":{"emoji":"🚫","category":"amazon"}}
---

# Amazon Negative Keywords 🚫

Strategic negative keyword management for Amazon PPC. Eliminate waste, improve ACoS, and maximize advertising efficiency.

## Installation

```bash
npx skills add nexscope-ai/Amazon-Skills --skill amazon-negative-keywords -g
```

## Usage Examples

**Search term analysis and negative keyword identification:**
```
"Analyze my search terms and identify negative keywords - I'm seeing too much wasted spend on irrelevant clicks"
```

**Campaign waste reduction strategy:**
```
"My Amazon PPC campaigns have 40% ACoS but lots of irrelevant traffic - help me create a negative keyword strategy"
```

**Savings estimation and optimization:**
```
"Calculate potential savings from negative keyword optimization across my 15 Amazon PPC campaigns"
```

## Core Capabilities

### 1. Search Term Analysis & Waste Identification
- Comprehensive search term report analysis and performance evaluation
- Irrelevant traffic identification and click waste quantification
- Conversion pattern analysis and keyword performance segmentation
- Cost savings opportunity assessment and ROI impact calculation

### 2. Strategic Negative Keyword Development
- Multi-tier negative keyword strategy development and implementation planning
- Match type optimization and negative keyword list management
- Campaign-level and account-level negative keyword strategy coordination
- Competitive negative keyword analysis and market positioning protection

### 3. Automated Management & Performance Tracking
- Systematic negative keyword addition and management workflows
- Performance impact measurement and savings validation
- Ongoing optimization and refinement processes
- Cross-campaign negative keyword synchronization and scaling strategies

## How It Works

### Step 1: Search Term Analysis & Waste Assessment
*Comprehensive analysis of search term performance and waste identification*

Analyze search term data to identify optimization opportunities:
- Review search term reports across all campaigns to identify low-performing and irrelevant queries
- Analyze conversion patterns, ACoS performance, and traffic quality to quantify wasted spend
- Identify keyword themes and patterns that consistently underperform or attract wrong audience
- Calculate potential savings and ROI impact from negative keyword implementation

### Step 2: Strategic Negative Keyword Implementation
*Systematic negative keyword strategy development and deployment*

Develop and implement comprehensive negative keyword strategy:
- Create tiered negative keyword lists based on relevance levels and performance data
- Implement campaign-level and ad group-level negative keywords with appropriate match types
- Establish account-level negative keyword lists for universal waste prevention
- Coordinate negative keyword strategy across multiple campaigns for maximum efficiency

### Step 3: Performance Monitoring & Continuous Optimization
*Ongoing negative keyword management and performance tracking*

Monitor and refine negative keyword performance:
- Track performance improvements and cost savings from negative keyword implementation
- Continuously analyze new search terms and add relevant negative keywords to prevent waste
- Optimize negative keyword match types and expand lists based on performance data
- Establish automated workflows for ongoing negative keyword management and optimization

## Output Format

```
## Amazon Negative Keywords Optimization Report
**Account:** [Account Name] | **Analysis Period:** [Date Range] | **Campaigns:** [Number] | **Potential Savings:** $[Amount]/month

### Search Term Performance Analysis

**Overall Traffic Quality Assessment:**
- **Total Search Terms:** [X,XXX] unique terms analyzed
- **Relevant Terms:** [X,XXX] ([X]%) - Converting or showing purchase intent
- **Irrelevant Terms:** [X,XXX] ([X]%) - No relevance to products/brand
- **Wasted Terms:** [XXX] ([X]%) - High spend, zero conversions, poor relevance
- **Current Waste:** $[Amount] monthly spend on irrelevant/non-converting terms

**Cost Impact Analysis:**
- **Total Monthly Ad Spend:** $[Amount]
- **Wasted Spend:** $[Amount] ([X]% of total spend)
- **Average CPC on Waste:** $[X.XX] (vs $[Y.YY] on relevant terms)
- **Potential Monthly Savings:** $[Amount] ([X]% improvement opportunity)

### Negative Keyword Identification & Categorization

**Tier 1: High-Priority Negative Keywords (Immediate Implementation)**

**Category 1: Completely Irrelevant Terms**
| Search Term | Impressions | Clicks | Spend | Conversions | Reason for Negative |
|-------------|-------------|--------|-------|-------------|-------------------|
| [irrelevant term 1] | [X,XXX] | [XXX] | $[XXX] | 0 | No product relevance |
| [irrelevant term 2] | [X,XXX] | [XXX] | $[XXX] | 0 | Wrong category |
| [irrelevant term 3] | [X,XXX] | [XXX] | $[XXX] | 0 | Different use case |

**Category 2: Wrong Intent/Audience**
| Search Term | Clicks | Spend | CVR | ACoS | Issue |
|-------------|--------|-------|-----|------|-------|
| [wrong intent 1] | [XXX] | $[XXX] | 0.1% | N/A | Information seeking |
| [wrong intent 2] | [XXX] | $[XXX] | 0.2% | N/A | Price comparison only |
| [wrong intent 3] | [XXX] | $[XXX] | 0.0% | N/A | Academic research |

**Category 3: Competitor/Brand Protection**
| Search Term | Impressions | Clicks | Spend | Strategy |
|-------------|-------------|--------|-------|----------|
| [competitor brand] + [product] | [X,XXX] | [XXX] | $[XXX] | Protect brand positioning |
| [other competitor] + [category] | [XXX] | [XX] | $[XXX] | Avoid wrong associations |

**Tier 2: Medium-Priority Negative Keywords (Performance-B

Excerpt, first 6,002 characters of SKILL.md, verbatim from the audited commit. It is text from someone else’s repository, quoted so you can judge it before your agent reads it.

Install

Pinned to the audited commit 1bc9142

Download folder ↗
npx skills add nexscope-ai/Amazon-Skills --skill amazon-negative-keywords -g

Commands as the repository documents them: shown, never run by us. Our verdict covers commit 1bc9142374b1 only.

Works in

The author has not said which agents this skill supports, and we have not tested it in any.

Audit history

Every audit, every source change

  1. ✓SAFE B 89 / 100

    first audit · source 1bc9142374b1

README badge

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ModelsAtlas: SAFE BMODELSATLASSAFE · B
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Add this badge to your README

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Questions about Amazon Negative Keywords

What does the Amazon Negative Keywords skill do?
Free AI agent skills for Amazon sellers— keyword research, competitor analysis, listing audit & more. Works with OpenClaw, Claude Code, Cursor, Windsurf, Codex and any agent that supports the Skills format.
Is Amazon Negative Keywords safe to install?
The audit found nothing in the source that contradicts what it says it does, and graded it B (89/100). Grade A is held back for packages that have also passed a sandboxed behavioural run, which is why a clean skill reads B.
What can Amazon Negative Keywords access on my machine?
The audit observed no filesystem, network or shell use at all in its source.
How current is this page?
The grade is for one exact copy of the source (1bc9142374b1), read on 2026-10-19. The repository is watched, and a new audit runs when it changes — this is the first audit.

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