A deterministic attention and judgment engine for agent systems.
The live attention layer for Paperclip. Re-stacks approvals, issues, and agent signals into now, next, and ambient.
A modular prompt architecture for LLM behavior control. YAML-based framework for persona consistency, memory management, and attention guidance across extended AI conversations.
A bounded Python CLI for reflective observation, attention protection, and return-to-practice workflows.
🧬 Build consistent AI personalities with the Kotodama Framework, ensuring engaging, reliable interactions throughout your conversations.
Manage persistent memory for Claude Code with a markdown vault that updates, reflects, and improves your agent's knowledge over time.
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