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Customer Review Aggregator

ASecurity

Aggregate and analyze customer reviews from G2, Capterra, Trustpilot, App Store, and other platforms. Performs sentiment analysis, identifies pain points, extracts feature feedback, generates marketing claims, and compares competitor reviews. Use when users need review analysis, competitive intelligence, or customer feedback insights.

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  • Added September 8, 2026
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Security analysis

A100/100

Scanned September 8, 2026

npx -y skills add bg-szy/TOP-SKILLS --skill customer-review-aggregator --agent claude-code

Installs into .claude/skills of the current project.

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SKILL.md
---
name: customer-review-aggregator
description: Aggregate and analyze customer reviews from G2, Capterra, Trustpilot, App Store, and other platforms. Performs sentiment analysis, identifies pain points, extracts feature feedback, generates marketing claims, and compares competitor reviews. Use when users need review analysis, competitive intelligence, or customer feedback insights.
---

# Customer Review Aggregator & Analyzer

Pull reviews from multiple platforms and extract actionable insights with sentiment analysis, pain-point detection, marketing-claim extraction, and competitor comparison.

## Contents

- `references/sources.md` - supported platforms and sentiment dimensions
- `references/intake-prompts.md` - scope and data-collection prompts, example use cases
- `references/output-templates.md` - report templates for every analysis type

## Workflow

1. Define scope. Present the scope prompt from `references/intake-prompts.md` to capture product, platforms, competitors, analysis focus, and time period.
2. Gather review data. Offer the three data-collection methods (paste, CSV upload, URLs via WebFetch) from `references/intake-prompts.md` and collect the reviews.
3. Analyze sentiment. Score overall sentiment and feature-level sentiment using the dimensions in `references/sources.md`.
4. Identify pain points. Cluster negative feedback by theme, rank by frequency, and assign impact plus a recommendation.
5. Extract marketing claims. Derive evidence-backed claims from positive reviews, each with supporting quotes, a confidence level, and a use case.
6. Compare competitors. When competitors are provided, build the side-by-side comparison and surface weaknesses to exploit.
7. Analyze feature requests. Rank requested features by mention count, urgency, and competitor coverage.
8. Assemble the report. Populate the full analysis report and offer deliverable formats.

For all output formats and tables, see `references/output-templates.md`.

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