ruvnet/ruflo1 file

Managed Agent

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

Specification
Skill ID
ruvnet/ruflo/managed-agent
Publisher
ruvnet
Repository
ruflo
Installs
0
Files
1
Synced
Sep 23, 2026
How to use it

Open any RiverX project, open the Skills panel in the chat, and search for this identifier. The files are fetched from the source repository at install time.

ruvnet/ruflo/managed-agentInstalls these files
  • SKILL.md

What this skill tells the agent

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.
  1. 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.
  1. 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).
  1. List — mcp__plugin_ruflo-core_ruflo__managed_agent_list { limit? } — every session on the org (so you can see which are still running / billing).
  1. 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 }

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