openspace

name	openspace
description	Install and route through OpenSpace, the skill management layer for AI agents, so a host agent can retrieve/rank/load the right SKILL.md out of this jeo-skills catalog (~150 installed skills), then evaluate skill quality from real execution evidence and evolve skills via FIX/DERIVED/CAPTURED updates. Covers install-as-skill-finder, retrieve-a-skill, evaluate-quality, evolve-skills, and local-first hub share/import. Triggers on: openspace, skill finder, skill retrieval, find the right skill, rank skills, skill discovery, skill quality, evolve skill, FIX DERIVED CAPTURED, skill hub, openspace-mcp, DiscoverSkills, skill-discovery, delegate-task.
allowed-tools	Bash Read Write Edit Glob Grep
compatibility	Requires Python 3.12+ and an MCP-capable host (Claude Code, Codex, Cursor, OpenClaw, nanobot). Local search, evaluation, and evolution work without cloud access; sharing to the cloud hub needs an OpenSpace cloud agent key.
license	MIT
metadata	{"tags":"openspace, skill-management, skill-discovery, skill-retrieval, skill-evaluation, skill-evolution, mcp, agent-skills, quality-layer, cloud-hub","version":"1.0","source":"https://github.com/HKUDS/OpenSpace"}

OpenSpace

Use this skill when the real question is "how does this host agent find, trust, and improve the right SKILL.md out of a large catalog?" — not when the user just wants a single skill executed.

OpenSpace's own README frames it as "The Skill Management Layer for AI Agents": your skills keep growing, and OpenSpace helps you retrieve, evaluate, and evolve with every run. In this repo, that job is specifically: act as the skill-finder / skill-retrieval layer for jeo-skills — a host agent installs OpenSpace once, then asks it to search, rank, and load the right SKILL.md out of the ~150 skills already installed under .agent-skills/ (and copied into $HOME/.agents/skills), instead of an agent guessing from a flat skill list or a human maintaining routing rules by hand.

When to use this skill

• The user wants to install OpenSpace so a host agent can act as a skill-finder over an existing skill catalog
• The user (or an agent) needs to retrieve/rank the best-fit skill for a task out of many installed skills
• The user wants to know which installed skills actually work based on real execution outcomes, not just descriptions
• The user wants controlled skill evolution (FIX / DERIVED / CAPTURED) driven by evidence from real runs
• The user wants to share or import skills through a local-first hub (package browsing, explicit import, trust-gated upload)
• The user is choosing between OpenSpace and a plain catalog grep, a long-lived knowledge wiki, or per-repo agent memory

When not to use this skill

• The user only needs plain keyword/grep lookup across the existing skill catalog → route to codebase-search or semble; do not stand up a full MCP skill-management layer for a one-off lookup
• The user wants long-lived, synthesized markdown knowledge (concepts, indexes, research notes) → route to llm-wiki
• The user wants per-repo agent memory (handoff notes, decision logs, manifests) that is not about skill selection at all → route to opencontext
• The user just wants to run one specific, already-known skill → load that skill's SKILL.md directly; OpenSpace is for finding and judging skills, not a replacement for using them

Instructions