Skill Market

managed agent

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

GitHub
githubcommunityclaudemcpagent-runtimeagent-runtimes
0.0
0 installs73.4K GitHub starsby ruvnet

Skill Introduction

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

Core value

Turns reusable Debugging know-how into an installable skill, helping users complete github, community, claude, mcp work faster.

Target users

  • Developers, testers, and maintainers who handle Debugging tasks in Focus Code.
  • Teams that already trust workflows or content from ruvnet.
  • Users who want standardized prompts, steps, or conventions instead of repeating setup work.

Best practices

  • Read the skill content first to confirm required inputs, expected outputs, and dependencies.
  • Try it on a small task before relying on it for critical work.
  • Add project-specific constraints such as coding style, target platform, test expectations, and delivery format.
  • For external sources, verify the source link, version, and recent maintenance activity.

Best use cases

  • Tasks related to github, community, claude, mcp that need a reusable execution flow.
  • Converting a community repo, team convention, or personal workflow into day-to-day assistance.
  • Starting from a proven skill instead of writing prompts or procedures from scratch.

Limits and boundaries

  • Results depend on the quality of the original skill content and may need human correction.
  • It does not replace code review, tests, security review, or professional judgment.
  • External tools, APIs, account permissions, and local dependencies still need separate setup.

Differentiation

  • Structured around Debugging, making it easier to discover and reuse than loose prompt snippets.
  • Marked as GitHub, which helps users judge trust and maintenance expectations.
  • Keeps the original source link available for repository, documentation, or discussion follow-up.
  • Tagged with github, community, claude, mcp, so it can be filtered by concrete task intent.

Install and use

Install
Copy Install Command
focus install managed-agent-0e4807
View source

Detail Preview

SKILL.md

Primary filemarkdown5 KB

name: managed-agent description: Run an Anthropic Claude Managed Agent — a cloud agent harness (container + filesystem + tools), the cloud counterpart of the local wasm-agent runtime argument-hint: "<create|prompt|status|events|list|terminate> [options]" allowed-tools: mcp__claude-flow__managed_agent_create mcp__claude-flow__managed_agent_prompt mcp__claude-flow__managed_agent_status mcp__claude-flow__managed_agent_events mcp__claude-flow__managed_agent_list mcp__claude-flow__managed_agent_terminate mcp__claude-flow__wasm_agent_create Bash

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__claude-flow__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__claude-flow__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__claude-flow__managed_agent_status { sessionId } (idle/running/error) · mcp__claude-flow__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__claude-flow__managed_agent_list { limit? } — every session on the org (so you can see which are still running / billing).

  5. Terminate — mcp__claude-flow__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 }

Reviews

Overall rating

0.0
0.0

0 comments

No reviews yet