Repolode
제출하기
memodb-io

memodb-io/Acontext

Open-source memory layer that turns agent task outcomes into editable Markdown skill files shared across agents and LLMs.

GitHub에서 보기웹사이트
스타
3,695
포크
332
열린 이슈
37
마지막 커밋
3개월 전

어떤 프로젝트인가요?

Acontext is a skill memory layer for AI agents. It captures learnings from agent sessions, such as what worked, what failed, and user preferences, and stores them as agent skill files instead of opaque embeddings. Developers can read, edit, version, and export these files as ZIP archives for use with other agents, LLMs, or frameworks.

Learning is triggered when a task is marked complete or failed. An LLM pass distills the conversation and execution trace, and a Skill Agent decides whether to update an existing skill or create a new one according to a SKILL.md schema the developer defines. Agents retrieve memory through tools like get_skill and get_skill_file, relying on tool use rather than semantic top-k search.

The project provides Python and TypeScript SDKs, a CLI for starting a self-hosted backend with Docker, and a web dashboard. It also includes a virtual persistent disk, sandboxed code execution with mountable skills, and context engineering features such as summaries and editing strategies.

핵심 기능

  • 01Stores learned knowledge as Markdown skill files that can be read and edited directly.
  • 02Lets developers define memory structure through a SKILL.md schema.
  • 03Retrieves memory via get_skill and get_skill_file tools instead of embedding search.
  • 04Exports skills as ZIP for use with other agents or LLMs.
  • 05Provides Python and TypeScript SDKs and a CLI for self-hosting with Docker.

활용 사례

  • Giving a coding or support agent memory of user preferences that users can inspect and correct.
  • Letting an agent learn from failed tasks and reuse successful approaches in later runs.
  • Sharing one set of skill files across agents built on different frameworks.
  • Running a self-hosted memory backend for agent development and testing.

토픽

#agent-memory#llm#ai-agent#context-engineering#agent-skills#llmops#self-hosted#agent#agent-development-kit#agent-observability

자주 묻는 질문

Acontext은(는) 무엇인가요?
Open-source memory layer that turns agent task outcomes into editable Markdown skill files shared across agents and LLMs. Acontext is a skill memory layer for AI agents. It captures learnings from agent sessions, such as what worked, what failed, and user preferences, and stores them as agent skill files instead of opaque embeddings. Developers can read, edit, version, and export these files as ZIP archives for use with other agents, LLMs, or frameworks.
Acontext은(는) 무료로 사용할 수 있나요? 라이선스는 무엇인가요?
Acontext은(는) Apache-2.0 라이선스의 오픈소스입니다. 상업용 제품에 사용하기 전에 라이선스 조건을 확인하세요.
Acontext은(는) 아직 유지보수되고 있나요?
6개월 이내 업데이트. Acontext의 마지막 커밋은 2026년 7월 14일입니다.
Acontext은(는) 어디에 사용할 수 있나요?
Giving a coding or support agent memory of user preferences that users can inspect and correct. Letting an agent learn from failed tasks and reuse successful approaches in later runs. Sharing one set of skill files across agents built on different frameworks. Running a self-hosted memory backend for agent development and testing.
Acontext은(는) 어디서 받을 수 있나요?
소스 코드와 설치 방법은 GitHub에 있습니다: https://github.com/memodb-io/Acontext

요약은 프로젝트 README를 바탕으로 AI가 작성했습니다. GitHub 통계는 매일 갱신됩니다.

관련 프로젝트