octolens

What This Skill Does

The Octolens skill provides a powerful interface for the Octolens API, allowing the OpenClaw agent to monitor, aggregate, and analyze digital footprints across a wide spectrum of platforms. It acts as an intelligent bridge to real-time social listening, enabling users to track brand mentions, competitor activity, and market sentiment without manually visiting multiple sites. By leveraging advanced filtering, the skill parses data from Twitter, Reddit, GitHub, LinkedIn, and more, converting raw social data into actionable insights through sentiment analysis and engagement metrics.

Installation

To integrate this skill, use the command: clawhub install openclaw/skills/skills/garrrikkotua/octolens. Ensure you have an active Octolens account and an API key ready. Upon the first invocation, the OpenClaw agent will request your credentials, which are stored securely for session authentication via the Bearer token protocol.

Use Cases

This skill is designed for community managers, developer relations specialists, and marketers. Use it to:

• Monitor product mentions: Identify where your brand is discussed to engage with your community effectively.
• Sentiment tracking: Quickly filter for negative feedback to address potential PR issues or churn before they escalate.
• Lead generation: Use follower counts and engagement metrics to identify high-value prospects or influential voices in your space.
• Competitor Analysis: Track keywords associated with competitors to understand market positioning.
• Documentation/Bug tracking: Monitor Reddit or StackOverflow for discussions about specific features or bugs.

Example Prompts

1. "Check for any negative mentions of our brand on Twitter from the last 24 hours."
2. "List all recent mentions from GitHub where the sentiment is positive and the author has more than 500 followers."
3. "Fetch the latest discussions about our competitor's product launch from Reddit and summarize the common complaints."

Tips & Limitations

• Respect the rate limit of 500 requests per hour; if you are performing bulk analysis, try to batch your requests using the cursor-based pagination feature provided by the API.
• Use pre-configured 'views' to simplify complex, repetitive filter logic.
• The accuracy of sentiment analysis is dependent on the API provider's model; always verify critical insights manually.
• Ensure you check the X-RateLimit-* headers if you are running automated monitoring scripts within the agent.