메모리 및 지식 · DeepSeek Harness 플러그인 — 7 페이지

Evidence-driven learning memory and automation for Git-native AI agents

File-based memory plugin for DeepSeek Harness (DSH) — cross-session memory in transparent markdown files, with a memory star-map view

Desktop settings for encrypted personal local memory

DSH host-plane route booster for the nine security presets: infers the current (mode, phase) from the latest user message (sticky phase memory) and re-injects a compact governance envelope — gate checklist (from dsh-stage-gate GATES), review/double-sign reminder, boundary line, evidence-level pre-judgment, refs pointers or a forced-search nudge on miss — as a dynamic systemPrompt context contribution. A new snapshot lands only when the envelope text CHANGES (RuntimeContextProjection dedupes), so steady phases cost nothing.

DSH bundle plugin: mounts Project Memory skills, bootstraps memory architecture on first use, registers the /project-memory slash command, and prompts for memory compounding after tasks.

Curated, verified MCP server bundle for DeepSeek Harness (dsh): one install brings demo, memory, filesystem, GitHub, Playwright and remote HTTP MCP servers, with a connectivity verifier and CI checks.

DSH 全局自动记忆插件：会话开始注入记忆、memory_search 检索工具、压缩检查点自动落盘、漏网会话检测、设置界面配置（settings 命名空间 + client 半区）。

DSH 记忆插件：全局/项目两级记忆持久化，会话开始时注入系统提示词，设置页可视化面板（新增/修改/删除需用户确认），memory_query 只读查询工具。DSH web plugin: global/project memory with system-prompt injection, settings panel and a read-only query tool.

Native DeepSeek Harness tools for an Obsidian wiki vault: wiki_query, wiki_write, and wiki_lint implement the mechanical core (path routing, delta tracking, index/log bookkeeping, health checks) of the wiki skill suite.

Task-isolated long-term memory for DeepSeek Harness: remember / recall / search stay inside one task boundary, with optional prompt injection.

DeepSeek Harness 的 TencentDB Agent Memory 移植：L0 对话捕获 → L1 结构化记忆提取 → L2 场景/L3 画像，自动召回注入 + 记忆/对话搜索工具；复用现有 ~/.memory-tencentdb/memory-tdai 数据；附 Web UI 设置栏。

定时自动化 · 用量趋势 · 技能与 MCP Server 管理 · 自动沉淀的长期记忆——一套插件装齐 DSH 四个工作台。纯插件注入，不动官方源码，一句话安装。

One memory layer for every AI tool and agent, packaged for DeepSeek Harness with startup context, prompt-time recall, Mem MCP tools, and DSH thread capture.

Persistent 5-layer memory system for DeepSeek Harness (entry injection, relevance retrieval, agent tools, and LLM-backed auto-extraction).

Local-first personal memory and knowledge management for DeepSeek Harness

Cross-session plaintext memory plugin for the DeepSeek Harness — deterministic BM25 recall, writes take effect immediately, signal-driven injection, no embeddings

Enterprise workbench capabilities for the DeepSeek Harness — AI employees, knowledge bases, skills, MCP servers and plugins, all managed from local state

把 Codex（OpenAI Codex CLI / Desktop）的 MCP、技能、全局配置、记忆以适配 DSH 的形式迁移进 DeepSeek Harness（DSH 插件）

Adaptive Context Plane core bundle: Evidence Ledger + Governance + Context Composer + User Model (explicit)

CodeGraph for DeepSeek Harness (dsh): a Node bridge that exposes the codegraph Python CLI as dsh tools (callers / callees / deps / dependents / search / impact / overview / reindex) over a code index in SQLite.

Standalone DeepSeek Harness plugin: continual harness self-evolution. The agent persists and refines reusable prompt notes, memories, skill contracts, and subagent specs through small evidence-backed edits, with automatic refinement gates, rollback, and prompt injection.

DeepSeek Harness plugin (Cordis toolset) for reading, searching, and editing a local Obsidian vault, with optional Local REST API integration.

OpenViking retrieval, resource management, auto-recall and session memory for DeepSeek Harness.

DeepSeek Harness plugin: a read_graph tool backed by a codebase knowledge graph (CONTAINS / EXPORTS / IMPORTS / IMPORTS_SYMBOL).