#context-engineering

Project memory system for AI coding assistants (Claude Code, Cursor, Codex): session logs, project wiki, rules, TODOs, and handoff.

Open, MIT context format for AI coding agents: centralized .aigx/ rules + a per-file boundary index that targets the right rules, forbidden imports, and gotchas to each file. The only context format validated in a controlled benchmark. Tool-agnostic; nothing injected into your source.

Cut context bloat in your AI-agent stack: find and safely prune unused skills, MCP servers and subagents from real transcript evidence

🔁 Build reliable recurring AI-agent systems: 968 resources, 22 operational patterns, 22 loop contracts, 8 runtime starters, an interactive atlas, and a structured dataset.

Stop your coding agent reading the wrong files. Compiler-grade TS/JS repo map — 100% precision on blast radius vs grep's 60%, measured on public repos. CLI + MCP server, fully local, no vector DB.

Live context engine for AI agents: resolve verified workspace state before the context window opens. Pairs with Perseus Vault for persistent encrypted memory. Local-first, MIT. pip install perseus-ctx

The #1 Obsidian MCP for AI memory — freshness-aware, cited, local-first and read-only by default. Dataview, Bases, PDFs, every agent.

Claude Code memory system — auto context injection, drift detection, compounding, FTS5/vector search, Obsidian vault export. Zero core deps.

AILmanac — the always-current, community almanac for getting the most out of Claude and every AI. For all levels.

git diff for your agent's context window. See exactly what your LLM saw — turn by turn, block by block.

An interactive roadmap for harness engineering — building the agent loop, tool layers, context engineering, memory, retrieval, eval harnesses, and the rest of the scaffolding around modern LLMs.

See what your AI coding agent silently drops from its instruction files. A byte-exact truncation X-ray for AGENTS.md / CLAUDE.md / .cursorrules.

Local memory, context, and trust-boundary layer for cloud LLM coding agents

Evidence router & policy engine for coding agents — enforces source choice and proof-of-use through Claude Code hooks, including routes to MCP tools. Local-first; no LLM in the hook loop.

Best AI Code Architect 2026: Diagram-First Agent Orchestrator with AST Editing & Atomic Commits

Reusable Interpretable Context Methodology (ICM) workspace template for filesystem-based AI agent workflows

A self-improving agent-context framework for DeepSeek Harness

One markdown file. Two hooks. Memory that survives Claude Code's context compaction. Zero deps.

Odin Codex 2026: Outline-Driven AI Agent Workflows for Codex CLI

A Claude Code skill that builds and maintains a personal, file-based semantic layer as you work, and reloads it every session.

Agent context gate for Codex, Claude Code, Copilot, MCP, Cursor, Cline, Gemini and Windsurf repos

Local-first context cleaner for AI agents.

Skill Radar 2026: AI-Powered Smart Signal Triage for Claude Code

Transfer coding sessions between Codex CLI and Claude Code without losing context.

Persistent memory for Claude Code — your sessions distilled into a Google OKF knowledge bundle (plain markdown you own, not a database you're locked into) and injected back at the start of every session.

Beginner-friendly, technology-neutral AI coding workflow for Claude Code and OpenAI Codex—greenfield and existing projects.

🚀 ODIN Reflector 2026 – Next-Gen Meta-Reflection Engine for Outline-Driven AI Development

把一台 16G 的 Mac 跑成 Agent 生产系统：四 Agent Harness 全栈解剖——一个金融背景非程序员的 106 天工程记录

Just a lightweight lens for agent data and metrics. Built to scale past Claude when needed.

Run Claude Code as a teammate that owns work end to end. A maintained CLAUDE.md (works as AGENTS.md) plus a plan/execute/review skill pipeline with external verification, adversarial review, and structurally safe parallel execution. Dated changelog, updated when model behaviour changes.

A Rust-first CLI agent built for real work: durable sessions, multi-provider runs, governed tools, modular workflows, and a human checkpoint before software can change your system.

Technical product management case study for a governed AI context layer, covering architecture, validation, privacy controls, and reliable publishing.

The open-source context & reliability layer for AI agents — memory, lean context, guardrails, and multi-device sync in one self-hosted Rust binary.

AI-Zoll prepares, structures, and maintains the context that AI coding agents need to build software effectively. It does not write your application code — Claude Code, Cursor, Codex, and Copilot remain the builders. Zoll prepares the environment in which they build.

Best Claude Code Memory Toolkit Alternative 2026 – Smart Markdown Session Manager

Odin Gemini CLI 2.0: Outline-Driven Dev Skills & Agents 2026

Install a reasoning layer at the point of creation: one-line intent notes that tell AI (and humans) WHY code, plans, and content exist. Claude Code drop-in + tool-agnostic convention.

A Claude Code plugin for running coding tasks through phase-gated intentional compaction: every phase writes one self-contained artifact to disk, the next phase starts from a fresh session and reads only that artifact.

COMPASS — Commitment-Preserving, Position-Aware Semantic Substrate for LLM context

Less context. Full engineering rigor. A local-first, cross-agent engineering harness that cuts tool context without dropping required engineering gates.