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User Feedback Synthesizer

Checked
pmprompt·vlatest·productivity·MIT

This tool automatically analyzes user feedback to identify key themes and sentiments, streamlining insights for product improvement & decision-making.

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 pmprompt/claude-plugin-product-management --skill user-feedback-synthesizer -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

pmprompt

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 pmprompt/claude-plugin-product-management at 3114dbe33f.

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

Commit
3114dbe33f
Manifest
skills/user-feedback-synthesizer/SKILL.md
Scanned
1 file, 56 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

The user-feedback-synthesizer skill processes raw customer feedback to generate structured, actionable insights for product teams. It transforms unstructured text into organized data that highlights key themes and sentiment trends.

When to use it

  • Analyzing large volumes of support tickets or survey responses to identify recurring pain points.
  • Preparing concise summaries of user sentiment for weekly product roadmap meetings.
  • Extracting specific feature requests from open-ended feedback fields in your database.
  • Converting qualitative user comments into quantifiable metrics for stakeholder reporting.

Key capabilities

  • Synthesizes unstructured text into coherent, structured insights.
  • Identifies and categorizes common themes within disparate feedback sources.
  • Generates summaries suitable for immediate product management decision-making.

Example prompts

  • "Analyze these 50 customer support tickets and synthesize the top three recurring issues regarding the checkout process."
  • "Summarize the sentiment and key feature requests from this month's user survey responses into a bulleted list."
  • "Extract actionable product improvements from the raw feedback logs provided below, grouping them by priority."

Tips & gotchas

Ensure your input data is relatively clean to avoid synthesizing errors from typos or incomplete sentences. For best results, provide context about the specific product area you are analyzing so the agent can tailor its categorization logic accordingly.