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.
CTX Fit finds the cheapest AI coding setup that reliably works on your repository, then applies the winner as a reviewable change.
A calibrated context sieve for Claude Code: every tool result is judged by a System One model before it enters context.
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.
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.
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.
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
An inference-time framework for long-horizon LLM agents with explicit belief states, consistency validation, and trapping-aware recovery.