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Why Review

Checked
duc01226·vlatest·other·MIT

Analyzes product reviews to identify recurring themes, sentiment, and actionable feedback for improvement.

Repository

Install on your platform

Showing Claude Code. One command installs this skill into any of the agents below.

  1. 1

    Run this in your project

    terminal
    $ npx skills add duc01226/easyplatform --skill why-review -a claude-code

  2. Uses the open-source skills CLI and needs Node.js. Add -g to install it for your user instead of this project.

What we know about this skill

Publisher

duc01226

Taken from the source listing. We haven't verified who controls this account.

Install target

Live repository

Not pinned. Installing fetches whatever the repository holds at the time you run the command.

No human has reviewed this code. The checks below are a static scan of the files at one commit — nobody has run this skill or judged whether it works. A skill runs with whatever access you give your agent, so read the source before you install it.

Automated safety checks

scanned

This skill passed all 6 checks. We read its files at one commit and looked for the things that make a skill dangerous to run — not for whether it works.

  • Declares what it does: passed

    SKILL.md parses and declares a name and a description.

    SKILL.md exists, its frontmatter parses, and it declares a name and a description.

  • No undeclared network calls: passed

    Makes no network calls.

    Every host the skill dials — from its scripts, its config endpoints or the commands it tells the agent to run — is either well-known package and API infrastructure or declared in its own frontmatter. Links in documentation are not counted.

  • No obfuscated payloads: passed

    No encoded or obfuscated payloads.

    No base64, hex or compressed blob is decoded and then executed, and no encoded shell commands.

  • No credential access: passed

    Reads no keys, tokens, keychains or credential files.

    Neither the code nor the SKILL.md instructions read SSH keys, cloud credentials, keychains, token stores, browser cookie databases or dotfiles that hold secrets.

  • No pipe-to-shell installers: passed

    No pipe-to-shell or download-and-run installers.

    No `curl … | sh` pattern, in the code or in the instructions, that runs code fetched at run time.

  • Pinned to a commit: passed

    Scanned duc01226/easyplatform at b62343ca0c.

    The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.

Commit
b62343ca0c
Manifest
.agents/skills/why-review/SKILL.md
Scanned
1 file, 1,348 lines
This is a static scan, not a review. It reads the skill's files; it does not run them, and it cannot tell you whether the skill is any good or whether the code does what its description says. A skill runs with whatever access you give your agent.
What each check looks for →

About this skill

What it does

The why-review skill allows AI agents to analyze user feedback and identify underlying reasons or motivations. It can categorize feedback into different themes, extract key concerns, and provide summaries of the "why" behind a user's opinion. This helps understand not just what users are saying, but why they feel that way.

When to use it

  • Customer Support Analysis: Identify recurring issues and frustrations expressed by customers in support tickets or chat logs.
  • Product Feedback Prioritization: Categorize feature requests and bug reports based on the underlying user needs they address.
  • Survey Response Interpretation: Go beyond simple sentiment analysis to understand the reasoning behind survey answers.
  • Social Media Monitoring: Analyze comments and mentions to uncover the motivations driving public opinion about a brand or product.

Key capabilities

  • Feedback Categorization
  • Reason Extraction
  • Theme Identification
  • Summary Generation

Example prompts

  • "Analyze this customer support ticket and tell me why the user is unhappy."
  • "Summarize the reasons behind these negative survey responses."
  • "Categorize these comments about our new feature, focusing on the 'why' behind each one."

Tips & gotchas

The quality of analysis depends heavily on the clarity and detail provided in the feedback. Vague or ambiguous input may result in less accurate "why" explanations.