dsh-tdai-memory: TencentDB Agent Memory Plugin for DeepSeek Harness
dsh-tdai-memory is an MIT-licensed plugin (v0.2.14, requiring Node >=22.18) for DeepSeek Harness (DSH), designed to provide a long-term memory layer for the Web profile. It enables memory retention and structuring through L0 conversation capture, L1 structured memory extraction (facts/preferences/events), L2 scenario generation, and L3 user profile construction. The core functionalities of the plugin include automatically recalling and injecting relevant memories as dynamic context during prompt assembly, as well as providing two search tools: `tdai_memory_search` and `tdai_conversation_search`. The installation method is via `dsh plugin`.
Read Moredsh-memory: Integrating LingShu Long-Term Memory into DeepSeek Harness
dsh-memory is a DSH memory plugin maintained by FuRongJun-1999 that integrates the LingShu (AEIS) Spatiotemporal Memory Engine into DeepSeek Harness. It provides cross-session recall/search, a knowledge flywheel, a white-box reasoning pipeline, self-awareness, and a v3.3 role-playing engine, along with a guardrail charter and full-chain audit. Installation requires first installing aeis via pip, then adding the plugin using `dsh plugin --profile` and configuring `dbPath` and `tools` mode in `cordis.yml`. It is suitable for AGI and interpretability research-oriented developers. Before use, please review the source code and the MIT license.
Read MoreEngramory: A Portable Markdown Memory Protocol for DeepSeek Harness Agents
Engramory (tinqiao-oss/engramory) is a zero-infrastructure memory protocol designed for AI agents: Markdown-based single-file-per-fact structure, four types of typed notes, explicit curation discipline, and bounded indexing. It has 171 stars on GitHub and is categorized as a memory tool in SkillHub. This article introduces its core capabilities, official SkillHub installation command, the engramory_init initialization process, index guard configuration, and considerations like single-writer/experimental status, helping DSH users set up auditable long-term working memory.
Read Moredsh-mnemon: Building a Three-Layer Pluggable Memory Control Plane for DeepSeek Harness
dsh-mnemon is a DSH memory plugin maintained by omdsh-dev. It manages context, project files, and long-term memory through a three-layer division of Runtime, Documents, and Memory Spaces. The third layer can integrate with nine providers, including Mnemon. This article introduces its core capabilities, installation commands under DSH 0.1.1-rc.2, a 5-minute verification process, as well as permissions, data boundaries, and applicable scenarios, enabling quick evaluation for integration after discovery on SkillHub.
Read Moredsh-memory-evolve: Equipping DeepSeek Harness with Long-Term Memory and Self-Evolution
dsh-memory-evolve is a DSH memory-type plugin maintained by csyangwen, which provides capabilities such as five-track cross-session memory, git branch awareness, four-track to-do lists, skill self-evolution, COI external AI scheduling, and session collaboration in a purely plugin-based manner, with zero core modifications and zero runtime dependencies. This article introduces its positioning, core features, installation commands, and typical usage, while also explaining community directory attributes and security considerations.
Read MoreUsing memtrace-public to add codebase structure memory to DeepSeek Harness
# memtrace-public This codebase is compiled into a structured knowledge graph that supports millisecond-level queries, covering functions, classes, call edges and versions, for DeepSeek Harness to use across sessions without repeatedly reading files. Maintained by syncable-dev, the community repository is categorized under the "Memory" category, and it had 454 stars as of August 18, 2026. The indexing is implemented via local Rust + Tree-sitter; the Harness plugin package `dsh-plugin-memtrace` is licensed under MIT, while the core indexer is under a proprietary EULA and is currently in private beta. This article cross-checks the installation commands, MCP tools, Skills, licenses and telemetry boundaries against the GitHub repository page.
Read MoreInstall verified MCP servers for DeepSeek Harness at once with dsh-mcp-bridge
**Translation:** dsh-mcp-bridge is a DeepSeek Harness community plugin maintained by Edge-Echo, which packages the official @deepseek-ai/dsh-mcp-client and a curated set of MCP servers into an installable bundle. By default, only the "everything" demo is enabled, with presets annotated for memory, filesystem, GitHub, Playwright and remote HTTP services. A verify script and CI connectivity checks are added via the servers/ directory definition. The project is categorized under the memory taxonomy. This article covers the directory page, cross-verified installation commands from GitHub and npm, capability boundaries and precautions.
Read MoreUsing dsh-kb-sieve to Build Auditable Local Knowledge Base for DeepSeek Harness
`dsh-kb-sieve` is a memory plugin for DeepSeek Harness maintained by omdsh-dev, which builds local knowledge packages with original text citations and SQLite FTS5 from md/txt/docx/pdf files. This paper verifies the capabilities of the three tools `kb_build`, `kb_query` and `kb_read` by cross-checking with the directory page and GitHub source code, covers the installation commands on the directory page, as well as usage boundaries including the PDF dependency `pdftotext`, incremental building and permission risks.
Read MoreEquip DeepSeek Harness with Readable and Editable Cross-Session Memory Using dsh-mneme
dsh-mneme is a DeepSeek Harness memory plugin maintained by modusensus, licensed under MIT. It uses native SQLite with editable Markdown for dual-writing cross-session memory, and offers autoDream background consolidation and optional offline semantic retrieval. This article verifies the installation commands, seven memory_* tools, configuration options, and notes based on the community directory page and GitHub README: the plugin runs with current dsh privileges, requires Node 24+, and has entity extraction and Sleep Mode disabled by default.
Read MoreConnect PowerContext Memory Service to DeepSeek Harness via powercontext-dsh
### 翻译结果（符合技术文档规范）： powercontext-dsh is an Apache-2.0 licensed DeepSeek Harness memory plugin maintained by knqiufan. It connects to a running PowerContext Server via HTTP, providing recall, memory, handover, experience and skill capabilities without embedding storage or using MCP. This article verifies the installation commands, pc_* tools, `/pc` command, configuration items and security boundaries against the community directory page and GitHub repository.
Read MoreConnecting DeepSeek Harness to a traceable academic research workbench with dsh-scholar
DSH-Scholar is a DeepSeek Harness community plugin maintained by lzszq, licensed under MIT. It is categorized under the memory category on the catalog page, which emphasizes retrieving, reading and summarizing literature within the agent loop; while the repository describes it as a research workspace for pure computational research, integrating materials, conversations, experiments, evidence ledgers and TeX manuscripts into the same recoverable project. It is gate-only by default, and agents cannot approve关卡 (levels/checkpoints) on their behalf. This article checks the installation commands, standalone workbench, Runner and typical slash commands against the catalog page and GitHub repository.
Read MoreDistill DSH Dialogue Experience into Reusable Skills with distill
distill is a memory plugin for DeepSeek Harness maintained by LoserFox: it only hooks into agent/turn-stopping and does not add tools to the main conversation. After each round ends, the background subagent will review every 3 new user messages by default, and write reusable processes into SKILL.md marked with `distilled-by: dsh-distill`. The directory installation command is `dsh plugin add github:LoserFox/distill`. It has been reported that the current version 0.1.0 has an issue where custom session events cause failure to load chat history on dsh 0.1.0-rc.6. Please check the source code, license and Issues before installation.
Read MoreInstall Local Hierarchical Memory for DeepSeek Harness with dsh-mnemon
DSH-Mnemon is a memory plugin for DeepSeek Harness maintained by omdsh-dev (MIT License, current version 0.2.2). It divides runtime memory, retrievable project archives and Mnemon memory into three layers. It uses local SQLite by default, and also supports connecting to nine types of providers such as Mem0. This article checks the installation command against the directory page and GitHub, as well as the first verification steps, cross-agent sharing boundaries and security considerations.
Read MoreAdd Cross-Session Long-Term Memory to DeepSeek Harness with dsh-memory-evolve
`dsh-memory-evolve` is a DeepSeek Harness memory plugin maintained by csyangwen (MIT License, JavaScript). It uses five-track memory, git branch filtering and confirmation-based writing to沉淀 project conventions, user preferences and progress into `~/.dsh/memories/`, eliminating the need to repeat everything from scratch when switching sessions. Capabilities such as skill evolution, four-track todo, COI scheduling and session broadcasting are also provided in the same repository, and most of them are disabled by default. The installation command on the directory page is `dsh plugin add github:csyangwen/dsh-memory-evolve`. The community plugin library has no official affiliation with DeepSeek / Horizon Robotics (Fang), and you should check the source code and license before installing.
Read MoreAdd persistent memory to DeepSeek Harness agent using mnemon
Mnemon is a persistent memory for LLM supervised agents maintained by mnemon-dev: it uses local SQLite four-graph storage, the host model determines what to remember, and the binary is responsible for indexing and recall. The community directory categorizes it under "Memory" and marks it as featured. This article verifies the installation commands, DSH configuration entry, CLI usage, and the relationship with dsh-mnemon according to the directory page and GitHub.
Read More