$ loading_
Analyze game design, structure concepts, and improve AI workflows with evidence-first methods.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "ParanoiaSkills" yet — see the docs or source repo.
Use an evidence-first approach to analyze this game's core loop, progression feedback, and retention mechanics. Separate facts, inferences, and risks, then provide testable improvement suggestions.
A structured analysis report with mechanic breakdowns, evidence levels, issue diagnosis, and testable optimization directions.
Turn this game idea into a concept architecture. Output the core goal, player motivations, system modules, dependencies, and assumptions to validate, and highlight ambiguous areas.
A clear concept architecture document that aligns the team and reveals critical gaps.
Evaluate my current AI workflow for game design, identify inefficient steps, information gaps, and hallucination risks, then redesign it into a more traceable and reusable process.
An improved AI workflow plan with step definitions, control points, and reuse recommendations.
Curate and distill agent skills about people, relationships, memorial scenes, and methods.
Generate test scenarios and measure how well agents follow skills and rules.
Create, refine, and evaluate AI skills for better performance and triggering accuracy.
Create, refine, validate, and restructure AgentSkills and SKILL.md files.
Semantically search a local skill library and load only relevant skills on demand.
Discover, audit, and recommend the right skills for AI agents.