ParanoiaSkills
Enables structured analysis of complex systems through evidence-based frameworks, reducing design flaws and architectural debt before implementation costs ac…
GameDesignOS (formerly ParanoiaSkills) is a local-first system for AI-assisted game design. Version 1.1.0 ships 7 specialist skills packaged as Markdown (concept architecture, experience analysis, ED optimization, proposal writing, workflow evolution, and more), 17 contract schemas, 5 end-to-end workflows, and a deterministic local CLI runtime that tracks decisions, assumptions, evidence, and experiments with human approval gates. Works with Claude Code, Codex, OpenCode, and any Markdown-skill-capable agent.
- Ask Claude to analyze game design mechanics for balance issues and exploit vectors.
- Generate architecture diagrams for complex AI workflow systems from high-level requirements.
- Find evidence-based gaps in concept designs before engineering team reviews them.
Enables structured analysis of complex systems through evidence-based frameworks, reducing design flaws and architectural debt before implementation costs accumulate.
Game design teams and AI product architects evaluating concept feasibility and workflow dependencies.
https://github.com/DY-2026/GameDesignOS
By DY-2026
How to Get It
git clone https://github.com/DY-2026/GameDesignOS && cd GameDesignOS && python -m pip install -e . # installs the gamedesignos runtime CLI; the skill folders are plain Markdown and independently installable into your agent
Tip: Paste this into a Claude Code conversation. Verify command matches your Claude Code version.
After installing, paste this into Claude:
Analyze game design mechanics for balance issues and exploit vectors
Trust Signals Auto-scanned
Community Pulse New
No community discussions found yet. This doesn't mean the tool isn't good — it may be new or serve a niche use case.
Reviewer notes
Auto-scanned review. These are observations, not a security certification.
Scored from trust signals (evidence-eval-v1): 123 GitHub stars; contributors unknown; last commit 0d ago; license MIT.
Things to check
- Scanned, not hands-on tested — this entry was auto-scanned from public metadata (GitHub metrics, license, security flags). No reviewer has run it, and no tool-specific limitations have been documented yet.
- Single maintainer. Consider the risk if this person stops maintaining the project.
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Evaluation
Scored from trust signals (evidence-eval-v1): 123 GitHub stars; contributors unknown; last commit 0d ago; license MIT.