A comprehensive AI-driven system for collecting, analyzing, and tracking user feedback through automated surveys and sentiment analysis.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install ai-intelligent-feedback-collection
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install ai-intelligent-feedback-collection using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is AI Intelligent Feedback Collection?
AI Intelligent Feedback Collection is a robust tool designed to streamline the entire lifecycle of user sentiment gathering and data processing. As part of the Openclaw Skills ecosystem, it provides developers and product managers with a Python-based infrastructure to build visual questionnaires and automatically extract actionable insights from user responses. By leveraging FastAPI for high performance, the system ensures that multi-channel feedback is captured efficiently, allowing teams to move from raw data to product improvements in record time.
AI Intelligent Feedback Collection Use Cases
- Automating the collection of customer feedback across multiple digital touchpoints.
- Conducting in-depth product research and market validation surveys.
- Performing large-scale sentiment analysis to gauge user experience and satisfaction.
- Tracking and managing issue resolution based on direct user input.
How AI Intelligent Feedback Collection Works
- Define your survey structure using the visual design system or structured templates.
- Deploy the collection hooks to gather data from various sources and user interactions.
- Utilize the built-in AI engine to process responses through automated sentiment and data analysis.
- Generate comprehensive reports that categorize feedback and identify key trends.
- Map analysis results to the improvement tracking system to ensure feedback leads to tangible changes.
AI Intelligent Feedback Collection Setup
To integrate this skill into your environment, follow these installation steps:
git clone https://github.com/openclaw-skills/ai-intelligent-feedback-collection
cd ai-intelligent-feedback-collection
pip install -r requirements.txt
python app.py
AI Intelligent Feedback Collection Data Schema & Taxonomy
The system organizes data into a structured hierarchy to ensure clarity between raw input and processed insights. Openclaw Skills users can expect the following data organization:
| Component | Type | Description |
|---|---|---|
| Survey Design | JSON/Schema | Defines questions, logic branches, and visual layout parameters. |
| Feedback Repository | Database | Stores raw multi-channel responses with timestamps and source tags. |
| Sentiment Metadata | Analysis Layer | Attaches emotional polarity (Positive/Neutral/Negative) to specific feedback nodes. |
| Improvement Logs | Tracker | Records the status of product changes linked to specific user feedback entries. |
AI Intelligent Feedback Collection Advanced Features
- Multi-channel data ingestion for unified feedback management.
- High-performance sentiment analysis utilizing AI-driven emotional recognition.
- Visual survey designer for rapid deployment of complex questionnaires.
- Scalable architecture supporting unlimited feedback volume on enterprise configurations.
- Automated issue tracking hooks to close the feedback loop within your development workflow.
SKILL.md
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