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Customer Review Aggregator

onewave-ai/claude-skills
191 installs168 stars
Summary

Pulls customer reviews from G2, Capterra, Trustpilot, app stores, and other platforms, then runs sentiment analysis to identify pain points, extract feature requests, and generate marketing claims backed by actual customer quotes. You can compare your product against competitors side by side, spot trends in what's breaking your NPS score, and build prioritized feature roadmaps based on what customers actually want. The output formats are practical: battle cards for sales, evidence-backed marketing claims, executive summaries. Works best when you need to turn hundreds of scattered reviews into actionable product or positioning decisions rather than manually reading through them.

Install to Claude Code

npx -y skills add onewave-ai/claude-skills --skill customer-review-aggregator --agent claude-code

Installs into .claude/skills of the current project.

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Notes, actions and memory. Without a meeting bot. First month 100% off.
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Files
SKILL.mdView on GitHub

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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Categories
Git & Pull RequestsCode Review & Quality
First SeenJun 3, 2026
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