OpenSpace

HKUDS's skill lifecycle layer for agents: retrieve the right skill per task, evaluate which ones actually work from real outcomes, share across agents and teammates, evolve with every run.

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Curator's take

The missing half of the skill ecosystem: everyone ships installers, almost nobody closes the loop on whether a skill WORKED. OpenSpace's bet is lifecycle — retrieval at task time, evaluation from real run outcomes, and evolution instead of repeat failures — across Claude Code, Codex, OpenClaw and friends. If your skill folder has become a junk drawer, this is the category to watch. NOT yet the standard: young v2, outcome-evaluation quality depends on how honestly your runs are scored, and the Feishu/WeChat-first community signals where the early adopters are. For plain install/audit needs, a simpler skill manager does less, more predictably.

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README.md

OpenSpace: The Skill Management Layer for AI Agents

Your Skills Keep Growing. OpenSpace Helps You Retrieve, Evaluate, and Evolve with Every Run

One Skill Management Layer to Power Them All — Claude Code, Codex, OpenClaw, Hermès, nanobot.

Why OpenSpace?

As your agent’s skill grows, can your agents:

🔍 Find the right skill at the right time?
✅ Know which skills actually work in real-world tasks?
🧠 Learn from failures instead of repeating the same mistakes?
🤝 Share successful workflows across agents and team members?
📚 Turn every completed task into reusable knowledge for the future?

OpenSpace manages the full lifecycle of your agent skills:

🔍 Retrieve — Find the right skill for every task.
✅ Evaluate — Know what works through real outcomes.
🤝 Share — Turn successful workflows into team knowledge.
🔄 Evolve — Improve skills with every run.

The right skill for every task. Proven by real outcomes. Improved with every run.

A private skill platform your org actually owns

🌐 One Skill Library Across All Your Agents

Your agents can retrieve, import, and reuse skills from one shared library—without rebuilding the same capabilities for every tool.

🔒 Your Skills, Your Data, Your Infrastructure

Deploy OpenSpace privately and keep your workflows, data, and reusable skill assets fully under your own control.

📈 Self-Evolving Skills, Proven by Real Outcomes

Use real task outcomes to keep what works, improve what falls short, and confidently retire what no longer delivers value.

One place to retrieve, evaluate, share, and evolve skills across all your agents.

📢 News

2026-07-17 🚀 OpenSpace v2 is released: Introducing the Skill Management Layer for AI Agents, with package-based browsing, quality summaries, task-trace uploads, and a refreshed dashboard and TUI.

Earlier news

2026-07-04 📊 Skill quality summaries now visible while browsing v2 skills: package and skill detail views show usage-quality summaries; public lineage pages display redacted placeholders for unavailable content.
2026-07-03 🔎 Package skill search and task-trace uploads are now first-class v2 flows: package pages sea

Continue your stack

What teams reach for next — and why each earns a place beside OpenSpace. Ranked by curator confidence.

Alternative to See all + compare →

asm

Scriptable skill manager for AI coding agents — install, search, dedupe-audit and security-scan skills across 19 providers, with --json/--yes on every command so agents and CI can drive it.

Why it fitsBoth manage agent skills across many hosts, split by ambition: asm is the scriptable package manager (install, search, dedupe, security-scan, --json for CI); OpenSpace adds the lifecycle — outcome evaluation and evolution — on top of retrieval.

SkillX

Research framework that auto-distills agent trajectories into a three-level skill knowledge base (planning, functional, atomic) — pluggable into weaker agents and new environments.

Why it fitsSame evolve-skills-from-experience thesis: SkillX is the research-grade trajectory distiller; OpenSpace is the product-shaped management layer with retrieval and team sharing around the same loop.