agentmemory-architecture
此技能详细阐述了 agentmemory 的架构、iii 引擎原语、存储模型、端口及可视化工具。它解释了记忆如何被存储、检索和管理，包括混合检索机制和记忆生命周期。开发者可利用此技能深入理解 agentmemory 的内部运作，从而更好地进行系统扩展、故障排查或优化记忆策略，确保 AI 智能体能高效地管理和利用知识。
npx skills add https://github.com/rohitg00/agentmemory --skill agentmemory-architectureBefore / After 效果对比
1 组在没有这个技能之前，开发者需要花费大量时间手动查阅代码、文档碎片或进行反复实验，才能理解 agentmemory 的复杂内部机制，导致学习曲线陡峭，系统扩展和问题排查效率低下。
该 Skill 提供清晰的架构概览和运作原理，使开发者能够迅速掌握 agentmemory 的记忆存储、检索和管理方式，显著缩短学习时间，加速开发和故障诊断过程。
agentmemory is a memory server for coding agents. It runs locally, captures observations, indexes them for hybrid retrieval, and serves them back over REST and MCP. It is built on the iii engine.
iii primitives
Everything is a function, a trigger, or worker state on the iii engine. There is no separate plugin system; the worker registers functions (mem::*) and HTTP triggers (api::*) and the engine routes calls. agentmemory does not bypass iii; new capability is a new function plus a trigger.
Retrieval model
Recall is hybrid: BM25 keyword search plus vector similarity plus graph expansion over linked concepts. The default install needs no API key because embeddings run on-device and BM25 needs none. An LLM provider only adds richer summaries and auto-injection, both opt-in.
Storage and lifecycle
Memories carry content, concepts, files, importance, and timestamps, grouped into sessions and optionally linked to commits. A lifecycle of capture, compress, consolidate, and forget keeps the store useful over time rather than letting it grow unbounded.
Ports
REST is the anchor at 3111. Streams = N+1 (3112), viewer = N+2 (3113), engine = N+46023 (49134). --instance N shifts the whole block by N*100.
Viewer
A real-time web viewer at http://localhost:3113 shows memory building as sessions run. Useful for demos and for confirming capture is working.
See also
- agentmemory-mcp-tools and agentmemory-rest-api for the surfaces.
- agentmemory-hooks for automatic capture.
- agentmemory-config for ports and feature flags.
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