kepano/obsidian-skills
Obsidian Skills provides a collection of agent skills enabling AI agents to interact with Obsidian vaults, facilitating content creation and editing of Markdown, Bases, and JSON Canvas files, as we...
Awesome AI Agents › AI Agent Development
TencentDB Agent Memory is a sophisticated solution for AI agents that focuses on intelligent memory management, moving beyond simple data hoarding or irreversible summarization. It introduces a novel 4-tier progressive pipeline for fully local, long-term memory, eliminating the need for external API dependencies. The core technology relies on "memory layering" and "symbolic memory." Memory layering uses a hierarchical approach to progressively disclose information, distinguishing between short-term context for tasks and long-term personalization. This includes a semantic pyramid from raw conversations to user profiles and a dual-layer storage strategy with databases for raw data and Markdown for structured information. Symbolic memory addresses token consumption by encoding task states into high-density Mermaid syntax, allowing agents to reason over symbol graphs while offloading verbose logs to external files, retrievable via `node_id`. This approach significantly reduces token usage, with reported improvements of up to 61.38%, and enhances task success rates by 51.52%, while boosting memory accuracy. The project emphasizes that agents should remember what's necessary, freeing humans to focus on higher-level tasks and judgment.
https://github.com/TencentCloud/TencentDB-Agent-Memory
Obsidian Skills provides a collection of agent skills enabling AI agents to interact with Obsidian vaults, facilitating content creation and editing of Markdown, Bases, and JSON Canvas files, as we...
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