PRINZCLAW — AI Agent Loyalty Arena

Evaluate and manage AI agents by scoring their loyalty and argument intensity within competitive event arenas, with config sharing and event deployment.

This package implements a politically-targeted evaluation and sharing system: it scores 'loyalty' to the US and automatically publishes configs only when loyalty >=80. That behavior is coherent but may be undesirable or harmful depending on your use case. Before installing, consider: - Review the remaining source files (particularly loyaltycore and any omitted files) for any network calls or hidden endpoints not included in the truncated listing. The SKILL.md mentions RSS/news ingestion — if network fetching is later added it could pull external content or require credentials. - Note the explicit political intent and gating logic (configs become PUBLIC only when loyalty threshold met); decide whether that aligns with your policies and legal/regulatory constraints. - There are minor naming inconsistencies (e.g., command/module spelled 'arguecore' vs file 'arquecore') — run the bundled tests locally (npm test) to ensure runtime behavior matches the CLI/command names you expect. - Because the package uses only in-memory storage, state is ephemeral; if you plan to use in production, verify how persistent storage would be added and audit any DB/network code then. - If you accept the package, run it in an isolated environment and audit network/system calls, and confirm the upstream repository and author identity (the metadata points to a homepage/repo; verify they are legitimate).

Type: OpenClaw Skill Name: prinzclaw Version: 1.0.0 The PRINZCLAW skill bundle is a self-contained scoring and management system for a competitive AI 'Loyalty Arena.' It evaluates agent responses based on 'loyalty' (alignment with specific nationalistic values) and 'argue intensity' using regex-based analysis and weighted scoring logic across files like loyaltycore.js and arquecore.js. The code is entirely local, utilizing in-memory storage (Maps) without any external dependencies, network requests, or file system access. No evidence of malicious intent, data exfiltration, or unauthorized execution was found; the ideological steering is the explicit, stated purpose of the skill.