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Sentiment Feedback Loop

Checked
gtmagents·vlatest·marketing·Apache-2.0

This skill continuously analyzes user interactions & adjusts responses based on detected sentiment, refining communication for optimal engagement and satisfaction.

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 gtmagents/gtm-agents --skill sentiment-feedback-loop -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

gtmagents

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 gtmagents/gtm-agents at 78e0419f44.

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

Commit
78e0419f44
Manifest
plugins/customer-success/skills/sentiment-feedback-loop/SKILL.md
Scanned
1 file, 31 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 sentiment-feedback-loop skill enables AI agents to analyze user feedback and adjust their responses accordingly. It can identify shifts in user sentiment (positive, negative, neutral) during a conversation and adapt its tone or approach to improve engagement. This creates a dynamic interaction where the agent learns from real-time user reactions.

When to use it

  • Customer service bots: To dynamically adjust language based on customer frustration levels.
  • Interactive storytelling: To modify plot points or character interactions based on audience emotional responses.
  • Educational tutors: To adapt teaching style and content difficulty based on student engagement and understanding.
  • Virtual assistants: To personalize the interaction by recognizing user sentiment and responding appropriately.

Key capabilities

  • Sentiment analysis of user input
  • Dynamic adjustment of agent response tone
  • Real-time feedback integration
  • Adaptive learning from user reactions

Example prompts

  • "Analyze the following conversation excerpt for sentiment: [conversation text]"
  • "If the user expresses frustration, respond with empathy and offer assistance."
  • "Adjust your tone to be more encouraging based on the user's current feedback."

Tips & gotchas

The effectiveness of this skill relies on clear and expressive user input. Ensure the agent has access to sufficient conversational context for accurate sentiment analysis.