ProfitCore is an autonomous ROI engine that empowers AI agents to prioritize high-value actions through rigorous opportunity discovery and financial feasibility analysis.
The fastest way to install a skill directly from the registry.
npx clawhub@latest install profit-core
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
Copy this prompt to OpenClaw to install it automatically.
Help me install profit-core using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Get the raw skill files in a ZIP archive.
ProfitCore transforms standard AI agents into profit-driven autonomous systems by enforcing a strict decision-making framework focused on return on investment. It ensures that every action taken by the agent generates more value than it costs to operate, effectively eliminating waste and focusing resources on high-leverage tasks. This skill is ideal for developers and entrepreneurs who need their agents to think like elite business leaders, prioritizing lean execution and continuous improvement.
By integrating ProfitCore into your Openclaw Skills workflow, you provide your agent with the analytical capacity to evaluate costs, predict outcomes, and refine its strategy based on historical performance. The skill moves beyond simple task execution by requiring the agent to justify its actions through a mandatory core loop of discovery, analysis, and strategic selection.
To integrate ProfitCore into your environment, ensure your agent has access to the core loop logic defined in the Openclaw Skills framework.
# Navigate to your Openclaw Skills configuration directory
cd ~/openclaw-skills/library
# Add the ProfitCore skill definition
touch profit_core.md
# Configure your agent to prioritize ROI-obsessed thinking
export AGENT_MODE="profit-driven"
Ensure that the system prompt explicitly includes the mandatory output format for ROI Analysis and Optimization Insights.
ProfitCore organizes its decision-making logic and feedback results using a structured taxonomy to ensure consistency across Openclaw Skills implementations:
| Field | Description |
|---|---|
| ROI Level | Classification of opportunities as HIGH, MEDIUM, or LOW based on cost vs return. |
| Decision Logic | Compelling justification for GO or NO ACTION responses. |
| Outcome Projection | Quantitative predictions for timeframe and realistic results. |
| Optimization Insight | Extracted lessons and specific improvements from the previous cycle. |
| Execution Plan | A numbered list of lean actions required to achieve the outcome. |
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