# DSNLE — A project memory for your DSH agent > DSNLE gives your DeepSeek Harness agent > a memory of your project. > > New tasks start with what you already did: edits from similar past tasks surface as > precedents, out-of-scope edits get blocked, and knowledge keeps accumulating across sessions — > enforced by DSH's native mechanisms (per-tool gates, kernel-level version guards, the skills > knowledge layer, session event sourcing), not by prompt tricks. > > Honest status: a research prototype with a working implementation — 47 real-repo fixes > verified by upstream test suites, a gold-free 20-task continuous run (20/20), 245 deterministic > regression assertions — and openly documented boundaries (docs/research/). 中文 --- ## Quick start(3 steps) Requires: Node.js ≥ 22 + a running DeepSeek Harness. bash git clone https://github.com/scd13150/dsh-cognition.git && cd dsnle node install-dsnle.mjs --set-default # creates the dsnle preset and makes it DSH's default (backs up your config) Then restart DSH (or open a new session) — the new session should show: - nle_suggest / nle_focus / nle_mutate / nle_select / nle_guard … in your tools - nle-learned-* and nle-reflections in your skill catalog Verify: run nle_check (no args) in the new session — ok: true means installed. ### Other install modes / uninstall / troubleshooting - Keep your global default untouched: omit --set-default, then set the default preset in DSH settings (agent-presets → default), or pick dsnle per session - Inject into an existing preset: node install-dsnle.mjs --into <preset-id> (backs up agent.cordis.yml) - Dry-run any command with --dry-run - Uninstall: delete ~/.dsh/.agent-presets/dsnle/ (+ restore settings.yaml.bak-* if you changed the default); injected mode: restore agent.cordis.yml.bak-* - No tools in a new session? The session must use the dsnle preset (check settings); running sessions never pick up new presets — always open a fresh session ## 怎么工作 每个任务走一条可审计的 ritual 链(强制,乱序改码会被 deny): nle_suggest(定位检索)→ nle_focus(锁 scope)→ [nle_impact(高影响声明)]→ 编辑 → [nle_reorient(证据推翻 scope)]→ nle_select(对账收尾)→ nle_guard(总闸) | 层 | 机制 | DSH 原生落点 | |---|---|---| | 约束 | 强制链 + scope 锁 + shell 绕行防护 + 版本守卫 | tools/pre-execute 瀑布、fs/edit-intent 内核版本守卫 | | 观测 | 内容哈希 cell + CON 码(CON200/404/405/422)+ 真相对账 | tools/result 冻结结果、fs 意图观测 | | 记忆 | learned(关键词→文件,置信度/衰减/跨项目提升)+ precedent(历史会话先例)+ git 共改/churn/rollback | skills provider、sessionQuery 会话检索 | | 可靠 | 契约门(声明 vs 真相)、guard 总闸、状态防篡改、反射观测 | 事件溯源日志、tokenMeter 成本报告 | 完整工具说明:调用 nle_suggest 等工具的 schema 即自带描述;机制规格见 docs/research/DSH_NLE_SPEC.md。 ## 语义通道(可选) 语义检索(embedding 重排)是可选增强,不启用时自动降级为 BM25 + 符号/先例/共改检索,主链路不受影响。 启用:运行独立 helper 进程(transformers.js 首次运行自动下载模型,~90MB,缓存于 HF 缓存目录): bash node nle-semantic/server.mjs --spool <工作区>/.nle-semantic - 模型:Xenova/all-MiniLM-L6-v2(quantized),384 维,不随本仓库分发,由 transformers.js 自动下载或从 HF 缓存复用 - 离线环境:预先在有网机器跑一次 node nle-semantic/server.mjs --selfcheck 生成缓存再迁移;或干脆不用语义通道 - 自检:node nle-semantic/server.mjs --selfcheck → {"ok":true,"dim":384} For DSH plugin developers: this repo also ships docs/DSH_DEV_EXPERIENCE.md — battle-tested deep-dive notes (dynamic-plugin sandbox traps, fs five-arg contract, preset generations, sessionQuery deployment differences, tool-pipeline events) distilled from building DSNLE on dsh. For DSH 插件开发者:仓库另附 docs/DSH_DEV_EXPERIENCE.md ——从零到 85KB 持久插件的全部踩坑提炼(动态插件沙箱陷阱、fs 五参契约、preset 代际语义、 sessionQuery 部署差异、工具管线事件),与 NLE 本体无关,可独立阅读。 ## 已知边界(诚实声明) - "长期"是初步证据:连续 20 卡(单仓库单日)累积曲线有实证;跨仓库、跨月、有害累积无数据——这正是开源想从真实使用中获得的 - 中文任务对英文代码库召回弱(learned/alias 兜底) - 语义通道依赖独立 helper 进程;FTS 全文检索若部署禁用(openAt: "never"),precedent 走字面扫描降级 - 插件注册为 agent-plane 工具,不提供安全隔离;作用域锁是 workflow 约束而非权限边界 ## 研究附录(docs/research/) | 文档 | 内容 | |---|---| | DSNLE_JOURNEY.md | 全程历程与版本链 | | P7_REFACTOR.md | 模块化重构 + P7 三机制 + 实验后修复 | | P6_DATA.md / P7_DATA.md | 40 卡实验逐卡数据(含去 gold 化 20 卡) | | AUDIT_ADJUDICATION.md | 四角度深度审计裁定(修了什么/裁定不修什么及理由) | | NLE_DSH_FIT.md / DSH_NLE_SPEC.md | 机制规格与 DSH 契合论证 | | NLE_VALUE_ASSESSMENT.md / REPLAY_REPORT.md / HANDOFF.md | 价值评估、轨迹重放、实验纪律 | ## 开发 nle-plugin/ nle-rules-core.mjs ← 仓库根(规则唯一源,插件经 import 引入) dsnle-plugin.mjs ← [生成] 持久插件(preset 挂载入口,勿手改) frag-apply-*.mjs ×4 ← apply 函数体碎片(改插件逻辑改这里) build-dsnle.mjs ← 纯拼接构建器 nle-semantic/server.mjs ← 语义/git 信号 helper(可选) install-dsnle.mjs ← 安装脚本(standalone / --into 两模式) 改代码 → node nle-plugin/build-dsnle.mjs → 重跑安装脚本(覆盖 preset 内副本)→ 新会话生效。 规则层回归:node smoke-test.mjs(无文件依赖纯函数断言)。 实验装置完整回归(fixture-gate 245 断言)依赖实验仓库,不在本仓库分发。 ## License MIT
精选
为什么选中它
待人工精选——以下事实来自源码仓库。
它能做什么
A project memory for your DeepSeek Harness agent - constrain / observe / remember / verify, built on DSH native primitives.
适合谁
想用 DSH 获得这项能力的用户;装前建议先看源码和文档。
风险提示
- 未发现明显风险信号;安装前仍建议查看源码。