by oceanbase · Codex Skill · ★ 708
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
PowerMem Persistent, self-evolving memory for AI agents and applications. English · 中文 · 日本語 PowerMem combines vector, full-text, and graph retrieval with LLM-driven memory extraction and Ebbinghaus-style time decay. It ships two-layer Experience + Skill distillation for self-evolving memory, multi-agent isolation, user profiles, and multimodal signals (text, image, audio). Why PowerMem AI agents need more than chat history. Context windows are finite, and naive "save everything" memory quickly becomes noisy, expensive, and hard to retrieve from. PowerMem turns conversations, actions, and feedback into structured long-term memory that can be searched, updated, decayed, and shared across agents. What makes PowerMem different: Intelligent memory lifecycle — LLM-driven extraction
| Stars | 708 |
| Forks | 84 |
| Language | Python |
| Category | Codex Skill |
| Quality Score | 47.3/100 |
| Open Issues | 41 |
| Last Updated | 2026-06-18 |
| Created | 2025-11-10 |
| Platforms | python |
| Est. Tokens | ~18k |
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powermem is PowerMem: AI Memory Plugin— Accurate, Agile, Affordable. Make AI Agent smarter.. It is categorized as a Codex Skill with 708 GitHub stars.
powermem is primarily written in Python. It covers topics such as agentic, agents, ai.
You can find installation instructions and usage details in the powermem GitHub repository at github.com/oceanbase/powermem. The project has 708 stars and 84 forks, indicating an active community.
The top alternatives to powermem on Agent Skills Hub include agentic-context-engine, Mysti, mira-OSS. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.