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OpenViking memory and context bundle for DeepSeek Harness: pre-step auto-recall and profile injection, session capture, `viking://` URI guarding, and recall/write memory tools backed by an OpenViking server.

AI 에이전트를 위한 LLM 감독형 영구 메모리로, 그래프 기반 회상, 세션 간 지식 공유, 단일 바이너리를 특징으로 합니다. DeepSeek Harness, Claude Code, OpenClaw 등 모든 에이전트 런타임과 함께 작동합니다.

Registers the local flowix-cli MCP server so the agent can search, read, create, and edit Flowix memos and mind-map artifacts.

PLUR memory for DeepSeek Harness — engrams injected straight into the prompt, no tool call required

Curated file-based long-term memory for DeepSeek Harness — human-readable markdown notes, one plain-file store shared across hosts (git-ignored when it lives inside a project repo), and a deterministic index cap enforced by ctx.tools.guard()

The Engramory curated-memory discipline as an installable plugin ([npm: dsh-engramory](https://www.npmjs.com/package/dsh-engramory)): a deterministic 200-line / 25 KB cap on the `MEMORY.md` index via `ctx.tools.guard()` — growth denied, a shrinking rewrite always passes — plus the protocol registered as a runtime skill. The store is plain markdown, one file per fact, shared with Claude Code, Codex, Kiro, and OpenClaw.

Noema long-term memory plugin for DSH: durable, inspectable agent memory with recall tools and a settings page.

Mnemon 심층 통합: 로컬 3단계 메모리(Runtime Memory, 검색 가능한 Documents, 감독형 Memory Spaces)를 제공합니다.

범위가 제한되고, 계층화되고, 승인 게이트를 거치는 감사 가능한 세션 간 메모리입니다: 타입이 지정된 `ctx.memory` 인터페이스, 의존성 없는 SQLite 프로바이더, `memory` 도구, 고정 스냅샷 주입을 제공하며, 모든 쓰기는 승인 게이트를 거치고 세션 로그에서 재구성 가능합니다.

Cross-session memory engine for DeepSeek Harness: SQLite store + human-editable Markdown mirror, autoDream consolidation, offline semantic search (local vector/rerank/clustering), entity-attribute-timeline, Sleep Mode, custom-model autoSummarize, and 7 memory tools.

Project-scoped cross-session memory: six-layer SQLite store (soul/user/project/fact/lesson/topic) on node:sqlite, cache-friendly first-message injection, memory_remember/search/find_similar/read/update tools, and per-window nightly consolidation ("dream").

Self-evolving team memory as plain Markdown in git: a native Cordis plugin that registers 38 bare-name memory tools plus a prompt-signals section re-evaluated at every assembly, with RPE reinforcement, decay and sleep consolidation; shares one data repo with its Claude Code (MCP) and OpenClaw hosts; verified against DSH 0.1.0-rc.6.

세션 간 메모리: 사람이 직접 편집 가능한 Markdown 미러를 갖춘 SQLite, 백그라운드 통합(중복 제거, 병합, 충돌 해결), 6가지 메모리 도구를 제공합니다.

기계가 읽을 수 있는 체크포인트와 낙관적 잠금(optimistic locking)으로 DeepSeek Harness, WorkBuddy, Claude Code, Codex 간에 영구적인 작업 상태를 이어갑니다.

Semantic retrieval, resource management, auto-recall (user + agent dual spaces) and session memory for DeepSeek Harness: memsearch/memfind/memread/membrowse/memgrep/memglob over viking:// URIs, memadd/memremove resource management, memqueue observer status, memcommit session capture, and memlearn skill playbook minting.

Technical-preview local graph memory for DSH and Codex: recalls owner-global and current-project evidence before each turn, writes USER and ASSISTANT records separately, and preserves project, session, actor, and source provenance for a visual atlas and cited knowledge pages.

Long-term memory & self-evolving plugin for DSH: L0 capture → L1 memory extraction → L2 scene grouping → L3 user persona, auto recall injection, skill synthesis, fully local (SQLite FTS5 + jieba, optional vector recall).

File-based cross-session memory: plain Markdown memory files with automatic retrieval injection, format-compatible with Claude Code's CLAUDE.md and memory files, so migrating is a manual file copy.

ShiGuang Memory Engine(SGME) 브리지: HTTP를 통한 멀티 에이전트 공유 장기 메모리 — L0/L1/L1.5/L2 정제, 시나리오 기반 주입, 통합 검색, 능동적 케어 시그널(memory_search / wiki_search / signal_pull / signal_claim / signal_ack), `dsh-sgme`로 설치 가능

모든 에이전트가 공유하는 단일 Obsidian 볼트: 의존성 없는 Python 코어(검색/승격/판정/폐기), 볼트 템플릿, dsh 플러그인(memory_search/show/submit/status)

CBDC 권한 게이팅이 적용된 제한적 로컬 메모리: SQLite + FTS5 클레임, 설명 가능한 use/verify/ignore 판단이 포함된 범위 기반 회상과 전체 감사 추적, /memory 명령어, 호출당 최대 3개 클레임/1200자 삽입, 추가 모델 호출 없음

Biomimetic memory system for DeepSeek Harness: plain-Markdown data layer, memory tools, frozen-snapshot injection, graded approval gating, structured audits, memory metabolism (dream), memory pins, semantic recall, /memory command, and cross-session retrieval.

Faithful port of the hermes-agent MEMORY.md / USER.md mechanism for DSH: bounded dual-bank memory (2200/1375 chars), a single `memory` tool (add/replace/remove/batch), frozen-snapshot injection per session, nudge reminders, DSH-native JSON storage — zero external dependencies, zero LLM cost.

프로젝트 범위의 세션 간 메모리: 첫 사용자 메시지에 PROJECT.md 스냅샷을 주입하고 memory_remember 도구와 ReAct 작업 후 자동 회고 제공, 프로젝트별로 독립된 메모리 파일 유지