Agent-Skills.md

Agent Skills: Customer Review Aggregator & Analyzer

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.

UncategorizedID: onewave-ai/claude-skills/customer-review-aggregator

Repository

onewave-ai/claude-skills
OneWave-AILicense: MIT
748

Install this agent skill to your local

pnpm dlx add-skill https://github.com/OneWave-AI/claude-skills/tree/HEAD/customer-review-aggregator

Skill Files

Browse the full folder contents for customer-review-aggregator.

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customer-review-aggregator/SKILL.md

Skill Metadata

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.