A sophisticated decision-support skill designed to provide objective, multi-angle analysis and stress-testing for high-stakes business and personal choices.
The fastest way to install a skill directly from the registry.
npx clawhub@latest install advisor
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 advisor using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Get the raw skill files in a ZIP archive.
The Advisor skill transforms your AI agent into a high-level consultant and trusted sounding board. It is specifically engineered to move beyond simple task execution, offering deep, balanced perspectives on complex scenarios like business pivots, career transitions, and investment strategies. By integrating this into your ecosystem of Openclaw Skills, you ensure that your agent doesn't just process data but actively helps surface blind spots and underweight risks.
This skill is built on a framework of clear thinking and zero-agenda analysis. It prioritizes the user's autonomy while providing the necessary friction to stress-test assumptions before major actions are taken. Whether you are navigating a corporate acquisition or a significant life change, Advisor provides the strategic layer required for professional-grade decision making.
To integrate this skill into your local environment, use the standard CLI installation for Openclaw Skills:
openclaw install advisor
Ensure your agent configuration includes the advisor capability in its persona definition to allow for autonomous triggering during decision-heavy dialogues.
The Advisor skill organizes data to track the evolution of a decision-making process. It uses the following taxonomy for its internal state:
| Attribute | Description |
|---|---|
context_depth |
Qualitative measure of the background information provided by the user. |
risk_vectors |
A mapped list of identified risks categorized by severity and probability. |
blind_spots |
Log of assumptions challenged during the session. |
recommendation_logic |
The underlying strategic framework used (e.g., SWOT, First Principles). |
outcome_projection |
Short-term and long-term impact analysis of the proposed decision. |
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