diff --git a/README.md b/README.md index ee4288f..2d13df3 100644 --- a/README.md +++ b/README.md @@ -140,9 +140,7 @@ When an AI agent performs poorly, the problem is not always the model. Sometimes - 🧩 Apply it to the right task - ✅ Choose the version that actually works -This problem becomes more serious as your skill library grows. - -With hundreds or thousands of skills, more choices can make the right skill harder to find. +This problem becomes more serious as your skill library grows. With **hundreds or thousands of skills**, more choices can make the right skill harder to find. Today’s agents can use skills—but they still struggle to manage them: - ❌ Poor retrieval — The right skill exists, but the agent fails to find it. @@ -155,15 +153,15 @@ Agents don’t just need more skills. They need to retrieve, evaluate, manage, a ## 🎯 What is OpenSpace? -**🚀 OpenSpace is a quality-first Skill Hub where real tasks teach agents which skills to trust, reuse, improve, and share.** +OpenSpace is the **Skill Management Layer** for AI Agents—helping them find the right skills, verify what works, and evolve your agents through real-world tasks. https://github.com/user-attachments/assets/1c6b1b44-b207-491b-ad23-0f0591c17e0a OpenSpace plugs into your agent as skills. -- **v1** helped agents learn, evolve, and share experience. +- **v1** enabled agents to learn from tasks, evolve skills, and share experience. -- **v2** adds the missing quality layer: every skill is judged by real task results, improved through controlled evolution, and shared with clear context — not just uploaded and forgotten. +- **v2** introduced the missing management and quality layer—so skills are continuously evaluated, improved, and shared with evidence instead of simply being uploaded and forgotten.
OpenSpace Skill Wiki package tree and skill search visualization @@ -171,29 +169,28 @@ OpenSpace plugs into your agent as skills. Skill Wiki turns shared skills into a searchable package tree with lineage and quality context.
-OpenSpace v2 gives agents four practical abilities: +## Four Capabilities for Managing Agent Skills -### 📊 Skill Quality from Real Tasks +OpenSpace gives agents four practical capabilities to manage the full skill lifecycle—from execution and evaluation to improvement and reuse. -Stop guessing. Know which skills actually work. +### 📊 Evaluate Skills with Real-Task Evidence +Stop guessing which skills work. Measure them through actual outcomes. +- ✅ Track every run — See whether a skill was selected, applied, completed, or replaced by a fallback. +- ✅ Monitor dependencies — Flag skills when their tools become unreliable, slow, or risky. +- ✅ Reuse with confidence — Prefer skills that consistently complete real tasks. +- ✅ Inspect the evidence — Review actual execution records instead of trusting descriptions alone. -- **✅ Task-result quality** — Every skill run is tracked: was it selected, applied, completed, or did it fall back? Over time, the pattern tells the truth. -- **✅ Tool reliability** — When a tool fails, slows down, or becomes risky, every skill that depends on it gets flagged — automatically. -- **✅ Quality-aware reuse** — A skill that consistently finishes real work is treated differently from one that keeps falling short. Your agent stops guessing. -- **✅ Clear evidence** — Instead of trusting a skill's description, users can inspect what actually happened across real runs. +**Skills earn trust by delivering results—not by looking good in a file.** -**A skill earns its place by working in the real world — not by looking good in a file.** +### 🧬 Evolve Agents with Skills +Skills should improve through experience, without creating uncontrolled changes. +- ✅ Evidence-driven updates — Use real task outcomes to decide what should be fixed, derived, or captured. +- ✅ Provisional by default — Let new skills prove themselves across tasks before becoming trusted. +- ✅ Validated releases — Check improvements before replacing a working version. +- ✅ Independent control — Manage a skill’s trust status and availability separately. +- ✅ Complete history — Track how and why each skill changes over time. -### 🧬 Controlled Skill Evolution - -Agents need to improve. But improvement without control is just chaos. -- ✅ **Evidence-driven updates** — Real task evidence decides when a skill should be fixed, derived, or captured. -- ✅ **Provisional first** — New evolved skills remain reusable but provisional until real cross-task success promotes them to trusted. -- ✅ **Independent trust** — Trust and availability are separate; a skill can be provisional or trusted while operators independently enable or disable it. -- ✅ **Validated skills** — A skill is checked before a new version replaces the old one. -- ✅ **Version history** — Users can see how a skill changed over time. - -**Agents should adapt to the real world, but every change needs control.** +**Let skills adapt to the real world—while keeping every change reviewable and controlled.** ### 🌐 Local-First Skill Hub