SkillsAdd

onewave-ai/claude-skills

customer-review-aggregator

Aggregate and analyze customer reviews from G2, Capterra, Trustpilot, App Store, and other platforms.

First seen Jan 24, 2026

Installation

$ npx skills add onewave-ai/claude-skills --skill customer-review-aggregator
View on skills.sh ↗ GitHub repository ↗

Summary

  • 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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Also in this package

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npx skills add onewave-ai/claude-skills
landing-page-copywriter 6K code-review-pro 2.5K csv-excel-merger 1.1K screenshot-to-code 1.0K technical-writer 971 social-media-content-repurposer 764 css-animation-creator 748 sports-betting-analyzer 666 knowledge-base-builder 633 job-application-optimizer 631

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More details

Agent compatibility

Declared targets from SKILL.md / docs. Unmarked agents are not listed — the skill may still install via the CLI.

Claude Code Not declared
Cursor Not declared
Codex Not declared
GitHub Copilot Not declared
Windsurf Not declared
Gemini CLI Not declared
Cline Not declared
OpenCode Not declared

Repository health

Stars 287
License MIT
Default branch main
Open issues 0
Status Active

Package contents

Files included with this skill beyond the listing page.

  • skill md SKILL.md 1,972 B
  • docs SUMMARY.md 370 B

History

  1. First seen on skills.sh
  2. First recorded snapshot · 302 installs

SKILL.md

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.