Trending repositories: context-window

8 tracked repositories tagged with context-window, ordered by stars. Use the topic filters below to narrow further.

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8 of 8 repositories

  • headroomlabs-ai/headroom

    Compress tool outputs, logs, files, and RAG chunks before they reach the LLM. 20% fewer tokens for coding agents, 60-95% fewer tokens for JSON, same answers. Library, proxy, MCP server.

    AI summary: An open-source platform for conducting and analyzing AI-driven user research interviews.

    65,316productivityPythonApache-2.0

  • headroomlabs-ai/headroom

    Compress tool outputs, logs, files, and RAG chunks before they reach the LLM. 20% fewer tokens for coding agents, 60-95% fewer tokens for JSON, same answers. Library, proxy, MCP server.

    AI summary: The context compression layer for AI agents, reducing tokens for tool outputs, logs, and RAG chunks.

    62,966ai-mlPythonApache-2.0

  • OthmanAdi/planning-with-files

    Persistent file-based planning for AI coding agents and long-running tasks. Crash-proof markdown plans, session recovery after /clear and compaction, per-turn re-injection against context rot, deterministic completion gate. Manus-style. Claude Code, Codex, Cursor, Kiro, OpenCode and 60+ agents via the Agent Skills standard.

    AI summary: A methodology and toolkit for persistent, file-based planning in AI coding agents.

    26,017developer-toolsShellMIT

  • humanlayer/12-factor-agents

    What are the principles we can use to build LLM-powered software that is actually good enough to put in the hands of production customers?

    AI summary: A set of principles and best practices for building robust, production-ready LLM-powered applications.

    25,108learningTypeScriptOther

  • mksglu/context-mode

    Context window optimization for AI coding agents. Sandboxes tool output (98% reduction), persists session memory, and enforces routing across 17 platforms via MCP + hooks.

    AI summary: A context window optimization tool that sandboxes AI agent tool outputs and enforces routing across 17+ platforms.

    19,690developer-toolsTypeScriptOther

  • mksglu/context-mode

    Context window optimization for AI coding agents. Sandboxes tool output (98% reduction), persists session memory, and enforces routing across 17 platforms via MCP + hooks.

    AI summary: A context optimization layer that intercepts AI tool outputs to reduce token usage and persist session memory.

    19,432developer-toolsTypeScriptOther

  • muratcankoylan/Agent-Skills-for-Context-Engineering

    A comprehensive collection of Agent Skills for context engineering, multi-agent architectures, and production agent systems. Use when building, optimizing, or debugging agent systems that require effective context management.

    AI summary: A comprehensive collection of skills and principles for engineering context and operating loops in production AI agent systems.

    17,627ai-mlPythonMIT

  • parcadei/Continuous-Claude-v3

    Context management for Claude Code. Hooks maintain state via ledgers and handoffs. MCP execution without context pollution. Agent orchestration with isolated context windows.

    AI summary: An advanced orchestration layer for Claude Code that prevents context loss through persistent memory and specialized subagents.

    3,879developer-toolsPythonMIT