v0.1.19 · MIT
Solo-style isolated brainstorm branches and Handoffs for DeepSeek Harness
v0.7.2 · MIT
DeepSeek Harness plugin and bundled Skill for safely evolving Cordis Candidates with Harbor.
v0.13.1 · MIT
DSH 费用统计插件:会话费用行 + 成本归因报告,llm-pricing 动态价格。 / DSH cost attribution and usage dashboard, priced by llm-pricing.
v0.6.0 · MIT
Update copilot for DeepSeek Harness: tracks the DSH core, bundled packages, and every installed plugin across npm and git, merged package-centric over all profiles, with one-click updates — the update command is identical for every profile. · DSH 更新助手:追踪
v0.5.5 · MIT
DSH plugin: run every agent shell command through Git for Windows bash on Windows instead of PowerShell. Replaces the pwsh executor with a Git Bash ctx.shell provider and materializes Git Bash variants of the standard/minimal/code/cordis agent presets int
— · Apache-2.0
One portable memory layer for every AI agent: local-first, Markdown-native, user-owned, and self-evolving across apps, tools, and workflows.
v0.1.2 · no license
Claude Code-style terminal UI for DeepSeek Harness agents, as an out-of-tree dsh plugin bundle
v1.3.5 · MIT
在deepseek harness中使用workbuddy api,因为公司只提供workbuddy积分
v0.1.3 · MIT
DSH 预设编辑器插件, 支持一键破甲.
— · MIT
Agent OS: the agent gets smarter on its own. We just hold the line: the grading command and expected result never make it into the success contract we hand it. Interview-gated, staged evaluation, budgeted evolution loop. MCP server, 13 runtimes: Claude Code, Codex CLI, Gemini CLI, OpenCode, Copilot, Kiro and more.
— · MIT
The world's first open-source AI-native vector design tool and the first to feature concurrent Agent Teams. Design-as-Code. Turn prompts into UI directly on the live canvas. A modern alternative to Pencil.
v1.4.1 · MIT
DeepSeek Harness (dsh) rules, commands & skills manager: /rules slash command, settings panel with visual rule editing, command list, user-defined custom commands (with {input} argument support, disable/enable), skill management (view/disable/enable/delet
v0.1.12 · MIT
微信读书 (WeChat Reading) integration for DeepSeek Harness: connect the official WeRead Skills Agent Gateway with a wrk- API key, then browse your bookshelf, export highlights & thoughts, query reading stats, and send highlights to flomo — agent tools plus a
v0.9.8 · no license
创建你的 AI 角色,进入你的故事世界。和角色聊天、冒险、穿书,让每一次互动都留下羁绊(支持 DeepSeek Harness 插件,欢迎使用)
v0.4.8 · no license
飞书/Lark 机器人桥接,同时支持 Pi 和 DeepSeek Harness(DSH)双平台,随时随地远程与你的编程助手对话
— · MIT
本地私有、开源的自进化跨平台 AI 内容发现 Agent:先理解你,再主动从 B站、小红书、抖音、YouTube、X、知乎、Reddit、微博等平台与开放 Web 寻找内容。(支持 deepseek harness 插件) | Local-first open-source cross-platform AI content discovery agent: understands you, then proactively finds content across Bilibili, Xiaohongshu, Douyin, YouTube, X, Zhihu, Reddit, Weibo and the open web.(support deepseek harness plugin)
v1.6.2 · MIT
An intent-calibrated DSH discussion mode that prevents complex conversations from drifting and turns them into evidence-based next steps.
— · MIT
DSH 插件雷达与精选榜:多路自动发现 9000+ 候选,容器真实安装路径运行级实测(四档判定),精选 Top 50 · 11 类人工策展,全量索引 PLUGINS-ALL.md,自动更新。
v3.1.9 · no license
一个自主的高级智能伙伴,不仅分析问题,更持续工作直到完成实现和验证。
v0.3.1 · no license
Delete DeepSeek Harness sessions from the UI: header danger button + sidebar session-row menu item (no conversation jump), risk-consent dialog with session name/id, stops running agents first, in-place list refresh without page reload. Works in web and the desktop client.
— · MIT
为纯文本模型"看图“设计更好的视觉工具箱和技能,支持多图理解,图片问答,前端UI还原、GUI 自动化等,并可选无缝接入多个主流agent,直接识别粘贴图片| A vision toolkit and skill designed for text-only llms — image Q&A, long-screenshot OCR, frontend UI restoration, and GUI automation, with optional seamless integration for Codex, Claude Code, Pi, Oh My Pi, and OpenCode
v1.9.0 · MIT
Lively Working-line extension for pi CLI and DSH
v0.1.0 · MIT
Open-source macOS record-and-replay workflow recorder for computer use agents. Captures mouse, keyboard, and UI events as structured traces so agents can learn, replay, and automate real desktop tasks.
— · no license
Open-source LLM knowledge platform: turn raw documents into a queryable RAG, an autonomous reasoning agent, and a self-maintaining Wiki.