noname-dsh-plugin：把项目记忆做成可审核的 DSH 工作流资产
noname-dsh-plugin 将 NoName Agent Harness 接入 DeepSeek Harness，在本机 SQLite 账本上管理追加式证据、分层记忆与品味审核。通过 noname_record、noname_remember、noname_package 与 noname_ledger 等工具，agent 留证与提议候选，人在本地网页签署后，下一会话可组装已批准上下文。需 Node.js 18+、Python 3.10+，从源码 build 后以 dsh plugin add 本地路径安装；插件以 dsh 进程权限运行，安装前应审阅 MIT 许可源码。
Read Moredsh-trilogy: Project Memory Plugin for DeepSeek Harness
`dsh-trilogy` is a Host plugin for DeepSeek Harness designed to address the lack of persistent memory in models. It enforces the maintenance of three Markdown files for each workspace: `PROJECT.md` (current state), `DECISIONS.md` (decisions), and `SESSIONS.md` (logs), with automatic creation, loading, and recording. The plugin provides tools such as `memory_checkpoint` for categorized logging, supports BM25 retrieval, and includes a graphical interface for memory management. Its core lies in an intelligent injection strategy: it controls priority via a budget, automatically injects context at session start, and weights categories based on activity. All routing is limited to local access, uninstallation does not delete data, and it is suitable for development scenarios that require long-term maintenance of project context.
Read MoreDeepSeek Harness Plugin: dsh-cognition (DSNLE) - Project Memory and Constraint System
dsh-cognition is a plugin for DeepSeek Harness (DSH) aimed at addressing agents' lack of persistent project memory. It leverages DSH native primitives to build a four-layer “constraint/observation/memory/verification” mechanism, including learned keyword mapping, historical precedent tracking, and Git change analysis. Users must install it in a Node.js ≥ 22 environment and execute tasks through toolchains such as `nle_suggest` and `nle_mutate`. The plugin supports optional semantic retrieval enhancement, but its recall for Chinese-language tasks over English codebases is relatively weak; it relies on a separate process and does not provide security isolation.
Read Moredsh-missher-memory: DeepSeek Harness Project-Level Memory Plugin
`dsh-missher-memory` is a standalone plugin designed specifically for DeepSeek Harness, aimed at addressing the tendency for architectural decisions and past solutions to be forgotten in long-running projects. Through structured management and a "review" mechanism, it provides project-level memory recovery, indexed retrieval, and reversible merging strategies to help developers maintain coherence in long conversations. After installation, it enables project or personal memory retrieval via the `memory_search` tool. The plugin stores data locally, does not modify core code, and is suitable for scenarios requiring deep development and historical reference.
Read Moredsh-project-memory: Add a verifiable, approval-required project memory for DeepSeek Harness
A common challenge in collaborative agent development is that the technical selections, constraints, and pitfalls encountered in one session are lost when the conversation moves to the next. You either have to re-explain everything from scratch each time, or let the model write to the memory file on its own. The risk of the latter is the lack of validation, meaning the content written by the model may no longer align with the current code. `dsh-project-memory` addresses this issue by transforming persistent decisions, constraints, agreements, lessons learned, and facts into versioned project records. However, the model can only propose these entries; whether they are committed to the records is decided by the human user. The philosophy behind DeepSeek Harness (DSH) is "Everything is a plugin." This plugin represents an extension of memory capabilities along this very line of thinking. # What is it? The positioning of `dsh-project-memory` can be summarized in a single sentence.
Read Moredsh-project-memory: Project memory plugin for DeepSeek Harness
dsh-project-memory is a persistent project memory plugin designed specifically for the DeepSeek Harness (DSH) agent. It resolves context loss issues in cross-session development by storing documents, code symbols, experience records, and task status on disk. Core capabilities include support for document memory (such as PDF/Markdown) and code symbol extraction with source code references, alongside optional integration of TypeScript for semantic enhancement. It employs a content hash-based automatic refresh mechanism and a read-time memory mechanism to achieve cross-linking between documents and code. Furthermore, it provides precise recall based on the BM25 algorithm with blind spot warnings and supports the selective filtering of experience records. Additionally, the TaskBridge functionality supports the binding, renaming, and status viewing of cross-session tasks. This plugin runs in a Node.js environment with no vector database dependency and is suitable for...
Read Morerxa3c/chat2skill: Extract project memory and reusable skills from assistant sessions
`rxa3c/chat2skill` is a plugin designed to address the issue of corrections, preferences, and project facts in assistant sessions failing to be stably accumulated. Its core functions are "post-session extraction" and "pre-session injection": by analyzing session signals, it distills information into local SQLite memory and `SKILL.md` skill files, automatically retrieving and injecting it in subsequent sessions. The plugin supports LLM mode (Proposer/Generator/Judge flow) and non-LLM mode (keyword detection). Data is stored locally, while the cloud is used solely for stateless execution and claims not to store data. Typical extraction requires approximately 4 LLM calls and is triggered only upon detecting correction or constraint signals. Documentation suggests it is best suited for Claude Code, Codex, and Cursor, while other agents require lifecycle support.
Read Moredsh-memoryhub: Integrate MemoryHub project memory into DeepSeek Harness
dsh-memoryhub is an MIT-licensed plugin for DeepSeek Harness (dsh), designed to address the issue of project memory usage across sessions. It integrates the `.memoryhub/` checkpoint memory maintained by MemoryHub into dsh sessions, supporting bidirectional data synchronization: automatically loading checkpoint memory upon session startup, while also allowing the current session to be saved back to MemoryHub via the `mh_save` command. The plugin registers six core tools (such as `mh_load`, `mh_save`, `mh_status`, etc.) and the `mh` workflow skill, providing a Memory tab in the Web UI for visualizing checkpoints.
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