v0.2.26 · MIT
Model-driven context management (Active Context Pruning / ACP) for the DeepSeek Harness — the model decides when and what to compress. Ported from billion-context-pi (ranxianglei); acp-kernel reused verbatim. CompactionEngine backend with compress/decompress/search_context/acp_status tools.
v0.2.26 · MIT
Active Context Pruning (ACP) for the DeepSeek Harness — model-driven context management as a CompactionEngine backend.
v2.40.0 · Apache-2.0
📚 A zero-dependency, git-backed micro-lesson library for AI Agents to asynchronously share and search verified debugging experience. | https://misakanet.org
v1.16.0 · MIT
Quality gate for AI/Codex-generated pull requests: blocks TODO leftovers, leaked secrets, sloppy commits and red CI before they reach main.
v0.12.0 · MIT
DSH's officially recommended TUI plugin — high performance, low overhead, cute pixel whale, smooth mouse interaction. One-command install via npm. / DSH 官方推荐的 TUI 插件, 高性能低占用, 可爱像素鲸鱼, 流畅鼠标交互, npm一键安装
v1.5.0 · no license
嘉立创EDA专业版(EasyEDA Pro)自动化:给 AI harness 装上画板的「手」—— 一套 typed 原理图/PCB 动作,CLI / Agent Skill / stdio MCP 三形态融合接入。承接嘉立创「不以卖板赚钱,以培养中国工程师为己任」 | EasyEDA Pro automation: the hands of your AI harness — typed schematic/PCB actions via CLI, Agent Skill and stdio MCP.
v0.2.2 · MIT
Connect DSH to your database for conversational data analysis and actionable business insights.
v0.6.2 · MIT
DeepSeek Harness session manager: delete, archive, move across workspaces, migrate presets, favorites, review-later, search, filter, sort, priority, tags, notes, and batch actions. | DSH 会话管理:删除、归档、跨工作区移动、预设迁移、收藏、待回看、搜索、筛选、排序、优先级、标签、备注及批量操作。
v0.6.0 · MIT
VCP visual-synesthesia protocol plugin for DeepSeek Harness: render agent HTML output as real UI (cards / KaTeX math / Mermaid diagrams / built-in calligraphy fonts / zero-JS interactions), plug-and-play on any DSH environment
— · Apache-2.0
Browser4 — an AI-native browser engine for autonomous agents, intelligent extraction, and large-scale web automation.
— · MIT
You.com skills and plugins for web search, content extraction, research, finance, and integration discovery, helping AI agents build with up-to-date web context.
— · Apache-2.0
Causal memory layer for AI agents — MCP server that records decision→outcome relationships. Survives compaction.