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managed-agent

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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SKILL.md(原文)

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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 }

レビュー

まだレビューはありません。使ってみた感想をお寄せください。

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