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Customer review aggregator

Skill bg-szy/TOP-SKILLS/skills/claude-skills/customer-review-aggregator

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.From its SKILL.md

Install
npx -y skills add bg-szy/TOP-SKILLS --skill customer-review-aggregator

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

2 things to look at

  • no licenseNo license file was found in the repository. Code published without one is not open source by default, so using it at work is a question for whoever answers licensing questions where you are.
  • 4 stars4 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

SKILL.md

1.9 KB, 309 tokens by cl100k_base, as published. Nobody here has run it

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.

What ships with it

Read from the repository

Just SKILL.md. No reference files, no scripts.

Keep looking

Skills are one crate of 326,790. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.