Memory

DSH 全局记忆插件：侧边栏「全局记忆」页，直接查看/编辑 ~/.dsh/AGENTS.md 与 ~/.dsh/memory/*.md。Host 半边注册 /api/dsh-memory 路由（回环限制），client 半边注入侧边栏入口与中心面板。热插拔挂载，不改 DSH 源码。

Persistent memory for DeepSeek Harness: memory read/write/retrieve tools, per-turn auto-recording, project-scoped recall injection and a management UI, with non-destructive Claude Code memory import.

Local-first Agent Experience Network for DeepSeek Harness, distilling task-level experiences from traces and live manifests, grading by H0-H4 evidence, discovering by compatibility, and promoting only after explicit review.

Cross-session memory plugin for DSH (v0.6.1, npm @asherliner/dsh-memory-connect): auto-extraction, SQLite FTS5 indexing, RRF semantic recall injected into the system prompt every turn, scheduled maintenance, LLM-powered consolidation via ctx.llm, context explosion prevention, and global Soul identity via ~/.dsh/soul.md. v0.5.0 added temporal context graph (valid_from/valid_until/supersedes, append-only corrections via reviseMemory), trust model (recalled history injected as untrusted reference, current instruction always wins), turn-end summarization. v0.6.0 added local semantic embeddings (BAAI/bge-small-zh-v1.5 via embed_server.py, cosine + RRF fusion with FTS5, no cloud calls, ~232 msgs/sec on CPU). v0.6.1 fixed ~ expansion in path config. Zero-config install.

Local, auditable personal memory for DeepSeek Harness: preferences, project conventions, workflows and error lessons persisted as a changelogged JSON file in the workspace, with onboarding, auto project-convention extraction and evidence-backed lessons.

Project memory for dsh with native task-system integration: session todos and file reads auto-condense into cross-session task records (task↔file links), so workflows are switchable and resumable without re-contextualizing. Read-time memory (no upfront scan): extracts code symbols, summarizes docs, and cross-links docs↔symbols; optional TS semantic enhancement (auto on when TS installed). Experience notes auto-dedup. Every recall includes a traceable citation. Pure JS, single dep, works out of the box, silent operation, zero overhead.

Small file memory for DeepSeek Harness. The model writes markdown, the host injects it.

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.

Layered file memory for DeepSeek Harness with workspace-scoped USER/MEMORY notes, background consolidation, and hybrid session recall.

Long-term memory for DSH agents — durable, inspectable memories with recall, search, browse and knowledge-graph tools, import from ten other AI coding tools, and a settings page.

Traceable, searchable cross-session memory for DeepSeek Harness — conversation knowledge as typed graph nodes (TASK/SKILL/EVENT) and typed edges.

DSH自记忆插件：结构化记录问题、方案与模型调用，支持加权检索、前提感知排序与外部导入。

DeepSeek Harness 分层长期记忆插件：瞬时/情景/语义三层记忆，自动捕获、AI 提炼、跨会话召回与可视化管理。

DeepSeek Harness (DSH) plugin for local-first automatic Wiki memory and native Skill generation.

DeepSeek Harness 上的反思层插件，把 Agent 的每一步记录成「假设→任务→结果」的证据链，蒸馏出以客观 done_when 为锚的可复用经验，让 Agent 累积每做一次就变好一点。

Automatic context compression for DeepSeek Harness: compresses tool outputs before they reach the model and keeps every lossy compression reversible via CCR retrieval tools.

Markdown folder long-term memory for DeepSeek Harness: one file per fact, an index line per memory, mounted into every request as a system prompt section

A typed, inference-capable ontology (TBox + ABox) plugin for DeepSeek Harness — durable domain knowledge the agent can define, assert against, and query under schema constraints.

DeepSeek Harness (DSH) plugin — inject context when user input or model output hits configured keywords, with toggleable/configurable rules and model-editable memory.

Project knowledge base plugin for DeepSeek Harness: Open Knowledge Format (OKF) bundles per project, agent search/read tools, a Web UI browser/editor, and a bundled OKF authoring skill

Industrial-grade 4-tier cognitive memory, red-light guard, and vector semantic engine for DeepSeek Harness (dsh).

Recent conversations stay vivid. Older ones fade into summaries, not oblivion. StrataGate gives DeepSeek Harness six-layer, time-decaying memory, while lasting events and relationships settle into a knowledge graph. Bring your memories from other AIs with you—no need to start over.

Local-first persistent memory for DeepSeek Harness: bounded pre-step hot-memory injection, exact and Chinese-bigram BM25 cold recall, six agent tools, approval-gated lease-lock writes with recovery receipts, and read-only governance and trajectory-review candidates.