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skill-discovery

Find reusable skills in OpenSpace's local registry and explore its cloud library when needed. Review matching skills, choose where to import them locally, and decide whether to follow them or delegate the task.

中文简介正在准备中。当前显示英语简介。

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Search reusable OpenSpace skills locally, and browse cloud packages step by step when a cloud skill may help. Reusing proven skills saves tokens, improves reliability, and extends your capabilities beyond built-in tools.

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适用场景

  • Finding a skill for a specific task
  • Checking which skills are available locally
  • Exploring cloud skills when local results are insufficient
  • Choosing between following a skill and delegating a task

包含的文件(2)

  • SKILL.md3.4 KB
  • .skill_id30 B

SKILL.md(原文)

安装前可以查看交给 AI 代理的指令内容。

Skill Discovery

Discover and browse skills from OpenSpace's local registry and cloud skill library.

When to use

  • User asks "what skills are available?" or "is there a skill for X?"
  • You encounter an unfamiliar task — a proven skill can save significant tokens over trial-and-error
  • You need to decide: handle a task yourself, or delegate to OpenSpace

Cloud access

search_skills is local-only. If the user wants cloud results, or a cloud operation reports a missing/invalid key, set up cloud access first and use cloud_browse_skills.

Ask for email and agent_name. Ask for password only through secure secret input; it must be 8 to 72 characters. Do not ask for passcode/OTP because cloud_auth_flow does not accept one.

cloud_auth_flow(action="bootstrap_agent_key", email="user@example.com", password="<secure-password>", agent_name="openspace-local-agent")

If secure password input is not available, ask the user to run:

openspace-cloud-auth bootstrap-agent-key --email user@example.com --agent-name openspace-local-agent

After setup, use cloud_browse_skills.

search_skills

search_skills(query="automated deployment with rollback")
ParameterRequiredDefaultDescription
queryyes—Natural language or keywords
limitno20Max results

cloud_browse_skills

Use this single cloud tool when local search is not enough. Continue calling the same tool with the returned next_actions[].action.

cloud_browse_skills(action="search_skills", query="automated deployment with rollback")
cloud_browse_skills(action="local_placement", query="automated deployment with rollback")
cloud_browse_skills(action="local_placement", local_category_path="technology/computing/deployment")
cloud_browse_skills(action="import_skill", cloud_skill_id="<cloud_skill_id>", local_category_path="technology/computing/deployment/rollback")

Use recall and pull_projection only when you need package discovery or package outlines before choosing a skill. Concrete skill search should start with search_skills.

Choose local_category_path for the user's local package taxonomy. It uses the same shape as cloud package paths, but is stored independently and may be more specific than the current cloud tree. Use local_placement to inspect existing paths and create a nearby child path before importing.

After search

Results are returned to you (not executed). Cloud imports return a local_path after cloud_browse_skills(action="import_skill", ...).

Found a matching skill?
├── YES, and I can follow it myself
│     → read SKILL.md at local_path, follow the instructions
├── YES, but I lack the capability
│     → delegate via execute_task (see delegate-task skill)
└── NO match
      → handle it yourself, or delegate via execute_task

Notes

  • This is for discovery — you see results and decide. For direct execution, use execute_task from the delegate-task skill.
  • Cloud skills have been evolved through real use — more reliable than skills written from scratch.
  • Always tell the user what you found (or didn't find) and what you recommend.

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