RAGFlow is a leading open-source Retrieval-Augmented Generation (RAG) engine that fuses cutting-edge RAG with Agent capabilities to create a superior context layer for LLMs
The Context Platform for your Data and AI Stack
A model-driven harness for AI coding agents: semantic modeling, app generation, progressive API Assist and evidence-based verification.
VCP 部署在 AI 模型 API 与前端应用之间,是面向AGI OS开发和探索的工业级基建示范项目。通过统一指令协议、多层级持久化记忆、分布式插件引擎及多 Agent 协作框架,将原本“无状态、无记忆、无工具调用能力”的大语言模型,彻底改造成拥有永久自我意识、物理世界操作权及群体协作智能的完整智能体系统。
Unbounded context. Memory that manages itself. One session, for life. The hippocampus for coding agents, part of CortexKit.
Team memory for engineers and their AI agents. Lives in your repo. Shared through Git.
天枢harness是一个的终端编程智能体,它要回答的核心问题是:模型何以稳定地交付——目标不漂移、完成有证据、验证有闭环,不说"应该修好了"。为此它在模型与真实世界之间建立一层认知执行环境(CVM),把目标、状态、证据、资源、权限与终止条件从对话历史中外部化,由运行时持续管理。同时对deepseek v4极度优化。
Project memory and workflows for Claude Code and Codex. Keep stories, plans, handovers, and review evidence in your repo. Resume across sessions and follow progress in the Mac app.
A Spring AI library that brings Claude Code-inspired tools and agent skills to your AI applications.
Composable, view-based memory for DeepSeek Harness. Pluggable sources and strategies, with three-tier memory out of the box.
CTX Fit finds the cheapest AI coding setup that reliably works on your repository, then applies the winner as a reviewable change.
Save tokens. Maximize context, Safely
Codex and Claude Code plugin (works in Claude Desktop): choose which past images go to the model with your next message. Unchecked images become placeholders, the conversation goes on, and requests stay small.
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.
Claude Code mod: hands off to a fresh conversation when context fills up, keeps the cache warm while you're away, and turns what you teach Claude into project notes
A calibrated context sieve for Claude Code: every tool result is judged by a System One model before it enters context.
dsh-sieve: context engineering & token optimization plugin for DeepSeek Harness (DSH) — tool output filtering, context pruning, progressive skill disclosure. 36% smaller payload in offline replay. DSH 上下文管理与 token 优化节省插件。
面向 AI 上下文管理的 Agent Skill:为 Codex 上下文管理、Cursor 上下文切换和 Claude 上下文管理提供跨窗口续接,用 Git 保存可验证的功能说明与变更记录。AI coding context management and agent handoffs.
Re-anchor long conversations that drift through repeated local corrections.
A Codex plugin and local MCP runtime for context-bounded image generation and inspection.
Safety-first GUI and CLI for auditing, backing up, importing, cleaning, and trimming Codex conversations without editing internal storage.
Deterministic, bounded local Git context as Markdown or JSON. Standard-library Python CLI.
The Biomimetic Context Engine & Neural Runtime for AI Coding Assistants
Local, read-only audit for stale AGENTS.md, CLAUDE.md, and generic SKILL.md instructions.
Builds up to a goal in a field you have no expertise in: splits it into the foundations that goal actually needs, mobilizes what you already hold, learns what is missing, and leaves every solved path behind for the next goal. Nothing is called done until a check passes.
Pensieve: never lose the thread. A local MCP server and Mac app that links your files, repos, agent sessions, tickets and messages into one thread per task, for you and your AI coding agents.
Cross-agent plugin for manually excluding and editing AI conversation context, with search, filtering, hide/restore, undo, and original Session preservation.
Branch from any answer and keep branching at any depth. Recursively isolated follow-ups that leave the main DSH task untouched.
扫出并清除「自称已废」的墓碑 skill、AI 幽灵碎片与死代码,统计释放的 Token 与磁盘。· An agent skill that reaps tombstoned skills, agent leftovers and dead code, reporting tokens reclaimed.
This is the official repository for the paper "ACM: Agentic Context Management for Long-Horizon Tasks" [https://arxiv.org/abs/2607.23809]
A minimal coding-agent harness built to measure what context management actually costs: constraint survival after compaction (8%→83%), default-FAIL verification against false completions, and KV-cache prefix design (21%→90%). Stdlib-only, real deepseek-chat runs
为 DeepSeek Harness 打造:选中 AI 回答或思考内容,随时追问、学习、检查与纠偏。
DeepSeek Harness 的 Agent 工作台扩展 · 多智能体协作、长上下文与记忆、代码理解、电脑操作。
An inference-time framework for long-horizon LLM agents with explicit belief states, consistency validation, and trapping-aware recovery.
DeepSeek Harness 用户记忆插件:跨会话保存原则、偏好与工作方式,按 token 预算注入。DSH memory plugin for persistent user preferences, explainable memories and budgeted prompt injection.