Gtm System

What This Skill Does

The Gtm System is a specialized Go-To-Market (GTM) tracking agent designed to streamline sales pipeline management for Expanso and Prometheus ecosystems. By integrating directly into the OpenClaw environment, this skill provides a robust interface to manage contacts, track opportunities, and monitor market signals. It acts as a central nervous system for business development, allowing users to move deals through defined pipeline stages—from initial awareness to final negotiation—while maintaining a structured database of interactions and upcoming tasks.

Installation

To integrate this skill into your OpenClaw environment, execute the following command in your terminal: clawhub install openclaw/skills/skills/aronchick/gtm-system Once installed, the system will initialize the workspace at /home/daaronch/.openclaw/workspace/gtm-system/ and configure the necessary SQLite database for your GTM records.

Use Cases

This skill is built for technical founders, sales engineers, and developers who need to track community sentiment and conversion. Key use cases include:

• Automating lead generation by crawling sources like HackerNews, Reddit, and GitHub for keywords.
• Maintaining a structured CRM within your terminal, avoiding the bloat of traditional SaaS platforms.
• Managing team follow-ups via automated daily action digests.
• Tracking the progression of technical sales cycles, such as trials or demos, with precise logging capabilities.

Example Prompts

1. "What are my priority actions for today, and do I have any pending reminders?"
2. "Add a new contact for Sarah Chen at TechCorp as a CTO, then create an opportunity for them labeled 'Interested in Bacalhau'."
3. "Run the crawlers for GitHub and Reddit, then show me the unprocessed signals that match my tracking keywords."

Tips & Limitations

• Database Integrity: Since the data is stored in a local SQLite file at /home/daaronch/.openclaw/workspace/gtm-system/data/gtm.db, ensure you back up this file regularly to prevent data loss.
• Signal Processing: The crawling feature is powerful but depends on the accuracy of your tracking keywords; refine your keyword categories and weights to reduce noise.
• Stage Consistency: Stick to the predefined pipeline stages (awareness, interest, evaluation, negotiation, closed_won, closed_lost) to ensure that your pipeline reporting remains accurate. If you require custom stages, you may need to extend the underlying Python script.