Nova权限系统

提供完整的权限认证系统，包括权限检查、身份管理、审批流程及权限配置模板，支持多平台账号绑定和审计。

Things to do before installing or enabling: - Don’t immediately copy the AGENTS.md rules into your global agent config. Back up AGENTS.md and other configs first. - Review the sub-skills' SKILL.md files: permission-gate and identity-management declare always:true which forces persistent inclusion — remove or change this flag if you don't want them always-loaded. - Inspect and test the Python code in a sandbox. There are multiple inconsistencies (e.g., some functions expect {"users": [...] } but bundled data templates are plain arrays). These will likely cause runtime errors or unexpected behavior. - Confirm and restrict filesystem permissions for /workspace/data, /workspace/config, and /workspace/logs (audit.log) because logs and user data may contain personal information. - Run the skill in an isolated test agent (not your production assistant) and exercise edge cases: missing open_id, malformed data, and approval flows. - If you accept the global-enforcement model, prefer manual configuration of AGENTS.md by a trusted admin rather than blindly pasting the provided block. - If you are not comfortable with skills that alter agent-wide behavior or force persistent inclusion, decline or modify the skill to be opt-in (remove always:true) and fix the data-format/code mismatches first.

Type: OpenClaw Skill Name: nova-permission-system Version: 1.0.3 The 'nova-permission-system' is a functional role-based access control (RBAC) and identity management framework designed for AI agents. It implements a 'gatekeeper' pattern using Python modules (main.py, middleware.py) and JSON-based data storage to manage user roles (owner, friend, stranger) and verify identities via secret codes. The skill bundle includes comprehensive instructions for the agent to enforce permission checks before executing sensitive operations and provides an audit logging mechanism (audit.py) to track security events. No evidence of data exfiltration, malicious code execution, or backdoors was found; the system appears legitimately designed to enhance the security of the AI environment.