A precision tool for AI agents to interpret DAO governance rules and map them to specific allowed or forbidden actions.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install governance-explainer
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install governance-explainer using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Governance Explainer?
The Governance Explainer is a specialized module designed for the Openclaw Skills ecosystem to decode the complexities of decentralized autonomous organization (DAO) policies. It serves as a bridge between formal governance text and practical operational execution, ensuring that AI agents and human users understand the boundaries of their authority. By providing a clear translation of dense regulatory language into plain-English constraints, it helps maintain protocol integrity and compliance.
This skill is essential for any autonomous system operating within a governed environment where actions have significant consequences. It prioritizes safety by defaulting to conservative interpretations and clearly distinguishing between explicit rules and inferred logic, making it a cornerstone for reliable Openclaw Skills implementations.
Governance Explainer Use Cases
- Validating proposed on-chain actions against existing community-approved governance rules.
- Clarifying the specific voting thresholds or role requirements for a new proposal.
- Assessing the reputational and operational risks of bypassing standard review processes.
- Onboarding new contributors by providing plain-language explanations of complex policy documents.
How Governance Explainer Works
- The skill accepts the raw governance rule text and the current context of the proposed action.
- It interprets the rule's intent to provide a simplified, plain-language summary.
- The AI analyzes the situation to generate a concrete list of allowed and forbidden actions.
- It identifies all necessary prerequisites, including specific roles, approvals, and vote thresholds required for the action.
- The system evaluates potential consequences, categorizing them into governance, operational, and system risks.
- It outputs a structured report or requests further clarification if the initial inputs are ambiguous.
Governance Explainer Setup
To integrate this capability into your agent, ensure your environment is configured for Openclaw Skills. You can register the skill using the following command:
# Register the governance-explainer skill to your agent
openclaw install governance-explainer --author "Morpheus"
Ensure that you provide both the governance_rule and the context as inputs during the invocation.
Governance Explainer Data Schema & Taxonomy
The Governance Explainer organizes its analysis into a structured format to ensure consistency across Openclaw Skills integrations:
| Property | Description |
|---|---|
simplified_explanation |
A high-level interpretation of the rule's intent in plain language. |
allowed_actions |
A list of specific actions that comply with the governance text. |
forbidden_actions |
A list of actions that explicitly violate the rule or policy. |
constraints |
Technical or procedural requirements such as vote counts or time-locks. |
consequences |
A breakdown of risk factors (Reputational, Operational, Systemic). |
Governance Explainer Advanced Features
- Safe-default logic: Automatically defaults to the most restrictive interpretation if the rule is ambiguous.
- Multi-vector risk assessment: Analyzes not just rule compliance, but the ripple effects on the entire ecosystem.
- Interpretation vs. Explicit tagging: Clearly marks which parts of the output are direct translations and which are logical inferences.
- Minimum-clarity querying: Optimized to ask only the most essential questions when data is missing, reducing agent chatter.
SKILL.md
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