About managed-agent
managed-agent is a skill for operating Anthropic Claude Managed Agents, a cloud runtime for long-running or asynchronous tasks. It covers agent, environment, and session setup, event inspection, package installation, and terminating sessions to limit ongoing costs.
Key features
- 01Create managed agents and environments
- 02Install container packages
- 03Send prompts and inspect events
- 04List and terminate sessions
- 05Track usage costs
Use cases
- 01Run tasks lasting minutes or hours
- 02Use cloud containers with network access
- 03Inspect a session's tool activity
- 04Find and terminate stale sessions
MCP support
The skill uses managed_agent_* tools to manage cloud sessions. It also explains how to attach reachable MCP servers to a managed agent.
Install
Copy the command and run it in a terminal.
npx skills add https:/ / github.com/ ruvnet/ ruflo --skill managed-agentAfter installing, type/managed-agentin Claude Code to confirm it loaded.
Details
From the project READMEManaged Agent (Anthropic cloud runtime)
ruflo-agent has two agent runtimes behind one mental model:
| Runtime | Tools | Use 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(orCLAUDE_API_KEY) in the environment, with Claude Managed Agents beta access.- If absent, every
managed_agent_*tool returns a structured "usewasm_agent_createfor a local no-key runtime" error — fall back to the WASM skill.
Steps
-
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 localruflo mcp startis 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.
-
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, raisemaxWaitMsor follow up withmanaged_agent_events. -
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 ofwasm_agent_files). -
List —
mcp__plugin_ruflo-core_ruflo__managed_agent_list{ limit? }— every session on the org (so you can see which are still running / billing). -
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. PassenvironmentIdto 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-trackingnamespace. - Treat orphaned sessions like leaked resources —
managed_agent_listthenmanaged_agent_terminateanything stale. - Beta API (
managed-agents-2026-04-01);multiagent/define-outcomeson 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 }