by greyhaven-ai · Codex Skill · ★ 957
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
turn repeated agent work into validated, reusable execution autocontext is a system for running scenarios, tasks, and missions, analyzing what happened, and carrying forward the knowledge that actually improved outcomes. The North Star is to move from one-off frontier-model exploration toward workflows that become more reliable, more auditable, and cheaper to run over time. The intended use is mostly hands-off: point the harness at a real task in plain language, let it work the problem, and then inspect the traces, reports, artifacts, datasets, playbooks, and optional distilled model it produces. What's New GEPA-inspired ASI/Pareto optimizer wired into improvement loop Component sensitivity profiling and credit assignment Pluggable scoring backends with Elo and Glicko support Novelty exploration and multi-basin playbook branching Cost-aware loop control and long-run presets North Star Most agent systems still start every run cold. They do not reliably preserve what worked, separate signal from noise, or turn repeated success into a reusable asset. autocontext is built to close that loop: run a scenario, task, or mission evalu
| Stars | 957 |
| Forks | 69 |
| Language | Python |
| Category | Codex Skill |
| License | Apache-2.0 |
| Quality Score | 50.892/100 |
| Last Updated | 2026-05-02 |
| Created | 2026-02-11 |
| Platforms | claude-code, codex, python |
| Est. Tokens | ~1402k |
These tools work well together with autocontext for enhanced workflows:
Looking for a autocontext alternative? If you're comparing autocontext with other codex skill tools, these 6 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.
🛰️ A CLI tool for tracking token usage from OpenCode, Claude Code, 🦞OpenClaw (Clawdbot/Moltbot), Pi, Codex,
#1 Persistent memory for AI coding agents based on real-world benchmarks
Manage multiple Claude Code, OpenCode agents from either TUI or Web for easy access on mobile. Also supports M
🦞+🔬: NanoResearch: The Autonomous AI Research Assistant
会记忆、能成长的随身 AI 助手 · 桌面 / 云端 / IM 随叫随到，手机远程也能连 | Personal AI that remembers and grows — lives on desktop, self-h
Claude Autoresearch Skill — Autonomous goal-directed iteration for Claude Code. Inspired by Karpathy's autores
Explore other popular codex skill tools:
autocontext is a recursive self-improving harness designed to help your agents (and future iterations of those agents) succeed on any task. It is categorized as a Codex Skill with 957 GitHub stars.
autocontext is primarily written in Python. It covers topics such as agents, ai, autoresearch.
You can find installation instructions and usage details in the autocontext GitHub repository at github.com/greyhaven-ai/autocontext. The project has 957 stars and 69 forks, indicating an active community.
autocontext is released under the Apache-2.0 license, making it free to use and modify according to the license terms.
The top alternatives to autocontext on Agent Skills Hub include tokscale, agentmemory, agent-of-empires. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.