Revenue OS is a Claude Code plugin for developers to discover ideal customer profiles, create value propositions, set pricing, and manage outreach. It automates monetization workflows from code to cash, benefiting startups and SaaS businesses. It connects to Claude for AI-driven insights and integrates with sales and marketing tools.
git clone https://github.com/Belkins/revenue-os.gitRevenue OS is a Claude Code plugin that automates the journey from product to revenue. It analyzes your codebase to identify ideal customer profiles, creates compelling value propositions using proven frameworks, designs psychology-backed pricing tiers, and generates ready-to-use outreach sequences for cold email, LinkedIn, and Twitter. The plugin includes competitive intelligence, landing page copy generation, objection handling, and a full revenue readiness audit. Built for indie hackers, solo founders, startup developers, and SaaS builders who struggle with monetization despite having strong products.
[{"step":"Install the Revenue OS plugin in Claude Code by running `claude plugins install revenue-os` in your terminal. Ensure you have access to your company’s CRM or customer data (e.g., HubSpot, Salesforce) for accurate insights.","tip":"Use the `--debug` flag during installation to verify the plugin is pulling data correctly from your connected tools."},{"step":"Define your goal and parameters in the prompt. Specify the action (e.g., 'discover ICP'), company context, and any constraints (e.g., 'target enterprise clients in Europe').","tip":"Be as specific as possible with your [SPECIFIC_GOAL] to avoid generic outputs. For example, instead of 'SaaS companies,' use 'SaaS companies in the cybersecurity space with 500+ employees.'"},{"step":"Run the prompt and review the output. Revenue OS will generate actionable insights like ICP criteria, value propositions, pricing tiers, or outreach sequences.","tip":"Cross-check the output with your existing data. For example, if Revenue OS suggests a pricing tier, validate it against your historical sales data using tools like Excel or Google Sheets."},{"step":"Integrate the insights into your workflow. For example, upload the prioritized lead list to your CRM or share the value proposition template with your marketing team.","tip":"Use the plugin’s export feature to generate CSV or JSON files for easy integration with tools like HubSpot or Salesforce."},{"step":"Iterate based on feedback. If the outreach sequence isn’t converting, refine the messaging using Revenue OS’s AI-driven suggestions and test a new version.","tip":"Track performance metrics (e.g., open rates, conversion rates) and feed them back into Revenue OS to improve future outputs."}]
Go from side project to paying customers as an indie hacker
Find product-market fit faster for early-stage SaaS
Monetize open source developer tools with pricing strategy
Generate complete sales assets and outreach in 2 weeks
No install command available. Check the GitHub repository for manual installation instructions.
git clone https://github.com/Belkins/revenue-osCopy the install command above and run it in your terminal.
Launch Claude Code, Cursor, or your preferred AI coding agent.
Use the prompt template or examples below to test the skill.
Adapt the skill to your specific use case and workflow.
Use the Revenue OS plugin in Claude Code to [ACTION: discover ideal customer profiles / create value propositions / set pricing / manage outreach] for [COMPANY_NAME], a [COMPANY_DESCRIPTION]. Focus on [SPECIFIC_GOAL: e.g., 'high-growth SaaS startups in the fintech space' or 'enterprise clients in the healthcare sector']. Provide actionable insights and next steps, including [OUTPUT_FORMAT: e.g., 'a prioritized list of ICP criteria', 'a draft value proposition template', 'pricing tiers with justification', or 'an outreach sequence with messaging'].
For **FinTechFlow**, a B2B SaaS startup offering AI-driven fraud detection for mid-market banks, we used Revenue OS to analyze their ideal customer profile (ICP) and refine their monetization strategy. The plugin first cross-referenced FinTechFlow’s existing customer data with industry benchmarks, identifying that **banks with $500M–$2B in assets** and **existing AI/ML investments** were 3.2x more likely to convert. It then generated a value proposition focused on **ROI-driven messaging**: "Reduce fraud losses by 40% in 90 days with no upfront integration costs." The plugin also recommended **pricing tiers**—$15K/year for mid-tier banks and $30K/year for enterprise—based on customer lifetime value (CLV) projections. Finally, it drafted an **outreach sequence** for the sales team, including personalized email templates and a follow-up cadence. The output included a **prioritized lead list** of 120 banks matching the ICP, with contact details and engagement scores. The sales team reported a **22% increase in meeting bookings** within two weeks of implementing the recommendations.
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