How to Identify Feature Requests with OpenClaw
Feature request extraction with OpenClaw and ToolRouter. Mine app reviews for product insights.
Tool
OpenClaw processes app reviews at scale with a systematic, batch-oriented approach that is ideal for regular monitoring cycles. Run sentiment analysis, feature request extraction, and bug report identification in sequence to produce a complete review intelligence report in one session. Its automated workflow is particularly effective for teams that want to establish a monthly or quarterly review analysis cadence without manual overhead.
Connect ToolRouter to OpenClaw
1Install the CLI
npm install -g toolrouter-mcp2Call tools directly from OpenClaw
toolrouter-mcp call web-search search --query "AI tools"
toolrouter-mcp toolsSteps
Once connected (see setup above), use the App Review Analysis tool:
- Ask OpenClaw: "Extract feature requests from my app reviews"
- OpenClaw returns ranked feature requests from review data
- Identify the most impactful features to build next
- Add top requests to your development backlog
Example Prompt
Try this with OpenClaw using the App Review Analysis tool
Find all feature requests in my app reviews. Rank them by user demand and group duplicates together.
Tips
- Run this analysis before each planning cycle to keep your roadmap user-driven
- Look for feature requests that would convert 3-star reviewers into 5-star reviewers
- Compare feature requests across iOS and Android for platform-specific insights