MCPInstall

managed-agent

by ruvnetAI & Agents

Run an Anthropic Claude Managed Agent — a cloud agent harness (container + filesystem + tools), the cloud counterpart of the local wasm-agent runtime

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Install

Works with every agent the skills CLI supports.

npx skills add https://github.com/ruvnet/ruflo --skill managed-agent
  1. 01

    Install

    Run the command in your project. The CLI asks which agents to install for.

  2. 02

    Describe the task

    Ask your agent for something this skill covers. It loads managed-agent automatically when relevant.

  3. 03

    Review the result

    The agent follows the SKILL.md steps, scripts and references bundled with the skill.

SKILL.md

The instructions your agent reads when the skill is triggered.

Managed Agent (Anthropic cloud runtime)

ruflo-agent has two agent runtimes behind one mental model:

RuntimeToolsUse it when
WASM (local, rvagent)wasm_agent_* / wasm_gallery_*fast, free, ephemeral, offline, untrusted code in a sandbox
Managed (Anthropic cloud)managed_agent_* (this skill)long-running / async work (minutes–hours), a real cloud container with pre-installed packages + network, persistent filesystem + transcript across turns

This skill drives the managed runtime — Anthropic's Claude Managed Agents (beta). The model: Agent (model + system + tools + MCP servers + skills) → Environment (container template) → Session (running instance) → Events (turns / tool-use / status, persisted server-side). See docs/adr/0001-wasm-contract.md and project ADR-115.

Prerequisites

  • ANTHROPIC_API_KEY (or CLAUDE_API_KEY) in the environment, with Claude Managed Agents beta access.
  • If absent, every managed_agent_* tool returns a structured "use wasm_agent_create for a local no-key runtime" error — fall back to the WASM skill.

Steps

  1. Create — mcp__plugin_ruflo-core_ruflo__managed_agent_create { model?, system?, name?, networking?, packages?, initScript?, mcpServers?, skills? } → { sessionId, agentId, environmentId, status }. Provisions Agent + Environment + Session. Save the three ids.

    • mcpServers: [{type:"url", url, name, authorization_token?}] — the cloud agent must be able to reach the URL. A local ruflo mcp start is not reachable from Anthropic's cloud; deploy/tunnel an HTTP ruflo MCP server first if you want the cloud agent to have ruflo's tools.
    • packages: {pip?:[], npm?:[], apt?:[], cargo?:[], gem?:[], go?:[]} — installed in the container.

  2. Prompt — mcp__plugin_ruflo-core_ruflo__managed_agent_prompt { sessionId, message, maxWaitMs? } → sends a user turn, polls the event log until the session goes idle (default 180s, capped 600s) → { finished, status, stopReason, assistantText, toolUses[], eventCount }. For very long tasks, raise maxWaitMs or follow up with managed_agent_events.

  3. Inspect — mcp__plugin_ruflo-core_ruflo__managed_agent_status { sessionId } (idle/running/error) · mcp__plugin_ruflo-core_ruflo__managed_agent_events { sessionId, raw? } (full transcript: user turns, agent thinking, tool_use, tool_result, status — the cloud counterpart of wasm_agent_files).

  4. List — mcp__plugin_ruflo-core_ruflo__managed_agent_list { limit? } — every session on the org (so you can see which are still running / billing).

  5. Terminate — mcp__plugin_ruflo-core_ruflo__managed_agent_terminate { sessionId, environmentId? } — always do this when done: a cloud session keeps billing container time + tokens until deleted. Pass environmentId to also delete the environment ruflo created.

Cost & safety

  • Managed Agents bill per session (LM tokens + container time) and are rate-limited per org. Estimate before a long run; record completed sessions to the cost-tracking namespace.
  • Treat orphaned sessions like leaked resources — managed_agent_list then managed_agent_terminate anything stale.
  • Beta API (managed-agents-2026-04-01); multiagent / define-outcomes on the agent config are research preview.

Quick example

managed_agent_create  { "model": "claude-haiku-4-5-20251001", "system": "Terse. Do exactly what is asked.", "name": "scratch" }
  → { sessionId: "sesn_…", agentId: "agent_…", environmentId: "env_…", status: "idle" }
managed_agent_prompt  { "sessionId": "sesn_…", "message": "echo hello > /tmp/x && cat /tmp/x — then stop." , "maxWaitMs": 60000 }
  → { finished: true, status: "idle", stopReason: "end_turn", assistantText: "Done.", toolUses: [{name:"bash", input:{command:"echo hello > /tmp/x && cat /tmp/x"}}] }
managed_agent_terminate { "sessionId": "sesn_…", "environmentId": "env_…" }
  → { sessionDeleted: true, environmentDeleted: true }

FAQ

What does the managed-agent skill do?

Run an Anthropic Claude Managed Agent — a cloud agent harness (container + filesystem + tools), the cloud counterpart of the local wasm-agent runtime

How do I install managed-agent?

Run npx skills add https://github.com/ruvnet/ruflo --skill managed-agent in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/managed-agent/ (personal) or .claude/skills/managed-agent/ (project).

Which AI agents can use managed-agent?

Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.

Is managed-agent safe to install?

No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.

Who maintains managed-agent?

It is published by ruvnet in ruvnet/ruflo. It has 596 recorded installs.

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