v0.8.9 · MIT
Task board plugin for the DSH web GUI: a sidebar entry plus a multi-column kanban view with real execution through DSH sessions, schedules, session rules and auto-cruise automation. Board truth lives on the host and syncs to every device over SSE (the bro
v0.1.7 · MIT
DSH 自动化插件:让 Coding 任务按计划在全新 Agent Session 中运行,并由用户或 Agent 创建和管理定时任务。 / Run coding tasks in fresh Agent sessions and manage schedules from DSH Web or an Agent.
v0.0.0 · MIT
Local MCP server for Google Workspace (Gmail, Drive, Calendar, Sheets, Docs, Contacts, Tasks, Meet, Search Console, +Forms/Chat/Admin) across multiple accounts — OAuth-only, encrypted token storage, deny-by-default writes.
v0.9.12 · Apache-2.0
Interactive long-session background agents plus persistent multi-agent team rooms for DeepSeek Harness: durable continuable child agents with progress, steering and interruption, and cross-session team rooms with a message bus, shared task board, approval
v0.2.16 · MIT
Visual Kanban board for DeepSeek Harness: Gitea and GitHub-backed tasks, workflow columns, and a dedicated agent session per task.
v0.14.5 · Proprietary
ClickUp MCP Server - Powering AI Agents with full ClickUp task, document, and chat management capabilities.
v0.8.0 · MIT
Your team and your AI agents work from the same context: tasks, their full history and time as plain files in your git repository
— · AGPL-3.0
AgentRQ: Human-in-loop realtime conversational task manager for AI Agents. Self-hosted! Control your own agents from wherever you want Mobile, Web, Desktop. Designed to work well with your own Claude subscriptions and any harness with ACP support.
v4.4.0 · MIT
AI-powered cascading development framework. Decompose complex projects into parallel executable tasks with auto-generated PRDs, design docs, and multi-agent collaboration (Claude Code, Codex, Aider).
— · AGPL-3.0
AgentRQ: Human-in-loop realtime conversational task manager for AI Agents. Self-hosted! Control your own agents from wherever you want Mobile, Web, Desktop. Designed to work well with your own Claude subscriptions and any harness with ACP support.
v1.3.1 · MIT
Deterministic, persistent graph server for tracking workflow state, decisions, and blockers.
v0.5.0 · MIT
把对话里说过的重要事情,变成持续可跟进的计划。 为 deepseek-harness 打造的个人助手:从对话中整理事项、跟踪变化,并在需要时提醒你。
v3.7.5 · Apache-2.0
Restore prior Claude Code AND Codex sessions with zero LLM calls. Cross-tool session handoff, cache-expiry prevention, real cost dashboard. One plugin, both hosts.
v1.3.1 · MIT
Deterministic, persistent graph server for tracking workflow state, decisions, and blockers.
— · MIT
Use when executing implementation plans with independent tasks in the current session
— · MIT
Long-horizon agent skill for Claude Code / Cursor / Codex / Grok Build — multi-task ledger loop, host-portable, clean-context supervisor, verified gates. Markdown library (loop-graph), not a framework.
— · MIT
Rigor Paper Context helper for README-first deep learning repo reproduction. Use only when the README and repository files leave a narrow reproduction-critical gap and the task is to resolve a specific paper detail such as dataset split, preprocessing, evaluation protocol, checkpoint mapping, or run
v1.2.0 · MIT
Claude Code skill for handling long-context tasks through recursive decomposition
v2.0.2 · MIT
Supports GPT Image 2, Seedance & ComfyUI, with a 1,400+ prompt library, carefully crafted hooks and a multi-task orchestration system
v0.7.12 · Elastic-2.0
Shared team knowledge, leaked-secret alerts, ranked code findings and tracked tasks, across every AI coding tool you use
— · Apache-2.0
Comprehensive Mastra framework guide for building agents, workflows, tools, memory, workspaces, and storage with current APIs. Use for documentation lookup, API verification, TypeScript setup, common errors, migrations, and `mastra api` CLI tasks: inspect or call resources on local, Mastra platform,
— · Apache-2.0
Run Codex and Cursor as background workers inside Claude Code. Reviews, tasks, and rescues with tracked jobs, live progress, and session handoffs.
v0.2.2 · MIT
Branch from any answer and keep branching at any depth. Recursively isolated follow-ups that leave the main DSH task untouched.
— · Apache-2.0
Self-evolving memory OS for LLM & AI Agents: ultra-persistent memory, hybrid-retrieval, and cross-task skill reuse, with 35.24% token savings and DeepSeek Harness support.