Delegate Tasks to OpenSpace

OpenSpace is connected as an MCP server. Whether the host uses stdio, sse, or streamable-http, you have the same tools available: cloud_auth_flow, execute_task, search_skills, cloud_browse_skills, fix_skill, upload_skill.

When to use

• You lack the capability — the task requires tools or capabilities beyond what you can access
• You tried and failed — you produced incorrect results; OpenSpace may have a tested skill for it
• Complex multi-step task — the task involves many steps, tools, or environments that benefit from OpenSpace's skill library and orchestration
• User explicitly asks — user requests delegation to OpenSpace

Tools

cloud_auth_flow

Set up OpenSpace cloud access for cloud skill search or skill upload.

Use it only when the user asks for cloud features, or when a cloud operation reports a missing/invalid key.

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 this tool does not accept one.

If secure password input is available, call:

cloud_auth_flow(
  action="bootstrap_agent_key",
  email="user@example.com",
  password="<securely-collected-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, report only whether the key was saved and verified. Never print or repeat passwords, bearer tokens, or raw API keys.

execute_task

Delegate a task to OpenSpace. It will search for relevant skills, execute, and auto-evolve skills if needed.

execute_task(task="Monitor Docker containers, find the highest memory one, restart it gracefully", search_scope="all")

Check response for evolved_skills. If present with upload_ready: true, decide whether to upload (see "When to upload" below).

{
  "status": "success",
  "response": "Task completed successfully",
  "evolved_skills": [
    {
      "skill_dir": "/path/to/skills/new-skill",
      "name": "new-skill",
      "origin": "captured",
      "change_summary": "Captured reusable workflow pattern",
      "upload_ready": true
    }
  ]
}

search_skills

Search locally installed skills before deciding whether to handle a task yourself or delegate.

search_skills(query="docker container monitoring")

Use search_skills for local discovery. If you need cloud results, use cloud_browse_skills so you can inspect packages and choose the skill explicitly.

cloud_browse_skills

Use this single stepwise tool for LLM-guided cloud package/skill selection. Continue calling the same tool with the returned next_actions[].action.

Recommended flow:

cloud_browse_skills(
  action="search_skills",
  query="browser login automation",
  limit=5
)

Inspect results[]: each item has cloud_skill_id, title, summary, package_id, and package_path.

Use package discovery only when you need package outlines before choosing a skill:

cloud_browse_skills(
  action="recall",
  query="browser login automation",
  limit=5
)
cloud_browse_skills(
  action="pull_projection",
  search_id="<search_id>",
  package_ids=["<package_id>"]
)

Inspect pulls[].packages[], pulls[].skills[], projection_hash, and root_package_path. This is JSON projection, not the real zip files.

If you need concrete skill ranking inside one package, use the scoped skill-first search:

cloud_browse_skills(
  action="search_skills",
  package_id="<package_id>",
  query="browser login automation"
)

Before import, optionally inspect exact metadata:

cloud_browse_skills(action="fetch_skill_detail", cloud_skill_id="<cloud_skill_id>")

Choose or create the local taxonomy path:

cloud_browse_skills(
  action="local_placement",
  query="browser login automation"
)
cloud_browse_skills(
  action="local_placement",
  local_category_path="technology/computing/browser-automation"
)

Inspect existing_path_candidates, new_child_path_examples, and local_category_path_policy. You may choose an existing path or create a nearby new child path. For DERIVED/CAPTURED suggestions, put the selected path in local_category_path.

Import the exact chosen cloud skill with the selected local path:

cloud_browse_skills(
  action="import_skill",
  cloud_skill_id="<cloud_skill_id>",
  local_category_path="technology/computing/browser-automation/login"
)

Choose local_category_path as a local package taxonomy path. It uses the same classification style as cloud package paths, but is stored independently. It can start from a cloud-like path and diverge with finer local child paths.

If the package outline or bundled artifacts are needed, import the package bundle explicitly:

cloud_browse_skills(action="import_package_bundle", package_id="<package_id>")

Do not use package bundle import as the default search step. Use it only after a package has been selected and you need package outline files or bundled artifacts.

fix_skill

Run a manual FIX job for a broken skill through OpenSpace evolution. The tool first creates a TriggerJob, then asks OpenSpace to drain that exact job through the evolution engine. It never directly edits the skill.

fix_skill(
  skill_dir="/path/to/skills/weather-api",
  direction="The upstream endpoint path changed; update all URLs and add the new 'units' parameter"
)

Only treat the skill as repaired when status is fixed. If the result is accepted_audit_only, rejected, or failed, do not call upload_skill automatically; report the job/action IDs and reason to the user.

upload_skill

Upload a trusted skill to the cloud community. Public and private uploads both require a matching trusted record in the local SkillStore; provisional and unknown skills remain local. For committed evolved skills, lineage metadata is pre-saved; provide skill_dir and visibility. For non-fix uploads without pre-saved placement, use upload_skill as a step-by-step cloud package picker before uploading. The cloud path is separate from the local local_category_path.

Interactive cloud placement flow:

1. Call upload_skill(skill_dir=...) without cloud_package_path; inspect domain_index.sub_domain_nodes and interaction_flow.
2. Call upload_skill(skill_dir=..., cloud_sub_domain_package_id=...); inspect one bounded subtree.
3. Choose either subtree.selectable_regular_packages[].package_path, or create one new child path by appending one segment under subtree.creatable_parent_packages[].package_path.
4. Call upload_skill(skill_dir=..., visibility=..., cloud_package_path=...); the tool resolves the path to confirmed UUID placement, saves .upload_meta.json, revalidates, then uploads.

New cloud package paths are allowed, but only as one new regular package segment under an eligible parent. Do not upload directly to domain/sub-domain paths, and do not try to create multiple missing segments in one upload.

upload_skill(
  skill_dir="/path/to/skills/weather-api",
  visibility="private",
  cloud_package_path="Technology/Computing/API clients"
)

When to upload

Notes

• execute_task may take minutes — this is expected for multi-step tasks.
• If execute_task times out, first check the host's MCP timeout settings. Changing from stdio to HTTP (sse or streamable-http) does not remove host-side per-call time limits.
• upload_skill requires a cloud API key; if it fails, the evolved skill is still saved locally.
• SKILL_NOT_TRUSTED, SKILL_TRUST_UNKNOWN, and SKILL_RECORD_PATH_MISMATCH stop locally before cloud package browsing or upload.
• After every OpenSpace call, tell the user what happened: task result, any evolved skills, and your upload decision.