4GitHub Trending (AI/LLM filtered)·
planning-with-files: persistent file-based planning layer for AI coding agents
A GitHub project implementing persistent, file-based planning for AI coding agents and long-running agentic tasks using crash-proof markdown plans that survive context loss. The system provides a deterministic completion gate and multi-agent shared state on disk, compatible with Claude Code, Codex CLI, Cursor, Kiro, OpenCode, and 60+ agents via a SKILL.md standard. The project has accumulated 24,602 stars with 61 added today, indicating meaningful community traction.
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Related events (8)
claude-mem: Persistent Cross-Session Memory Layer for AI Coding Agents
claude-mem is an open-source TypeScript library that provides persistent context across sessions for AI coding agents. It captures agent activity during sessions, compresses it using AI, and injects relevant context into future sessions. The tool claims compatibility with Claude Code, OpenAI Codex, Gemini, GitHub Copilot, and other coding agents. The repository has accumulated 78,579 stars with 319 added today, indicating strong community traction.
OpenAI releases Codex macOS app for managing parallel coding agents
OpenAI launched a native macOS application called Codex, designed as a command center for running multiple coding agents in parallel on long-horizon and background tasks. The app surfaces agent progress and decisions, clean diffs from isolated worktrees, and supports reusable skills and automations. It is available to ChatGPT subscribers with Codex access, with a limited-time trial for Free and Go tiers and 2x rate limits for Plus and Pro users.
claude-skills: 313+ Skill/Plugin Collection for Claude Code and Multi-Agent Coding Tools
A GitHub repository providing 313+ reusable skills, agent plugins, and workflow templates targeting Claude Code, Codex, Gemini CLI, Cursor, and eight other coding agents. Coverage spans engineering, marketing, compliance, C-level advisory, finance, and productivity domains. The project has accumulated 15,476 stars with 157 added today, indicating strong community traction. It represents a growing ecosystem of structured prompt/skill libraries designed to extend AI coding agents beyond pure code generation.
OpenAI releases Codex App for macOS: multi-agent coding command center
OpenAI launched the Codex App for macOS, a desktop interface for managing multiple coding agents running in parallel on long-horizon and background tasks. The app surfaces agent progress, clean diffs from isolated worktrees, and reusable skill automations, and integrates with existing Codex local and Codex cloud admin controls including RBAC and a compliance API. Enterprise and Edu users receive temporary 2x rate limit boosts as a launch promotion.
OpenAI blog: Jason Liu on using Codex for long-running agentic work
OpenAI published a case study featuring Jason Liu's workflow for using Codex to manage complex, long-running projects that extend beyond a single prompt. The post focuses on context preservation and project management techniques within Codex. It serves as a deployment/usage pattern showcase for OpenAI's coding agent.
obsidian-wiki: AI agent framework for building a digital brain via Obsidian using Karpathy's LLM Wiki pattern
A Python framework on GitHub enables AI agents to build and maintain a personal knowledge base through Obsidian, implementing Andrej Karpathy's LLM Wiki pattern. The project has accumulated 2,015 stars with 137 added today, indicating notable community traction. It sits at the intersection of agent memory management and personal knowledge tooling.
agentmemory: Persistent Memory for AI Coding Agents
agentmemory is an open-source TypeScript library providing persistent memory for AI coding agents, designed based on real-world benchmarks. The repository has accumulated 13,772 total stars with a notable single-day gain of 1,626 stars, indicating strong community traction. It targets the agent tool ecosystem by addressing memory continuity across coding agent sessions.
ARIS: Lightweight autonomous ML research agent using Markdown-only skills
ARIS (Auto-Research-In-Sleep) is an open-source Python project providing lightweight, framework-free Markdown-based skills for autonomous ML research workflows, including cross-model review loops, idea discovery, and experiment automation. It is designed to work with any LLM agent backend including Claude Code, Codex, or others. The project has accumulated 11,791 GitHub stars with notable daily traction (+106), suggesting meaningful community adoption.