Analyzing User Feedback

Name: Analyzing User Feedback
Author: refoundai

Checked

refoundai·vlatest·marketing·MIT

Analyzes user feedback to identify key themes and sentiment, helping you understand customer needs and improve your product or service.

Repository

Install on your platform

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

Run this in your project

terminal

$ npx skills add refoundai/lenny-skills --skill analyzing-user-feedback -a claude-code

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

refoundai

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 27 Sept 2026

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 refoundai/lenny-skills at 13598cc54e.
The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.

Commit: 13598cc54e
Manifest: skills/analyzing-user-feedback/SKILL.md
Scanned: 3 files, 737 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 analyzing-user-feedback skill enables AI agents to process and interpret user feedback effectively. It identifies common themes, sentiments, and actionable insights from text-based input such as reviews, surveys, or comments.

When to use it

To extract customer sentiment from product reviews for quality improvement.
To analyze survey responses and identify areas needing attention in a service or product.
To monitor social media feedback and gauge public perception of a brand or campaign.

Key capabilities

Sentiment analysis of text data
Identification of recurring themes or patterns in feedback
Extraction of actionable insights for improvement

Example prompts

"Analyze this customer review and identify the main sentiment and key issues mentioned."
"Summarize the common complaints from these survey responses."
"Extract insights from user comments about our new feature launch."

Tips & gotchas

Ensure feedback data is clean and relevant for accurate analysis.
Be aware that nuanced or sarcasm-heavy text may require additional context for proper interpretation.