Common Issues When Using Ruflo: A Technical Troubleshooting Guide

Most operational problems in Ruflo stem from configuration validation errors, task lifecycle failures, agent status mismatches, plugin execution errors, and MCP tool dispatch issues, all of which can be resolved by understanding the validation logic in ConfigTools.ts and the error handling patterns in Task.ts and Agent.ts.

Ruflo is an open-source orchestration framework that manages agent swarms and task execution through a layered architecture. When using Ruflo in production environments, developers frequently encounter specific failure patterns related to configuration validation, task execution, and agent lifecycle management. Understanding these common issues when using Ruflo requires examining the source code to see how the system validates inputs and propagates errors through its infrastructure layers.

Configuration Validation Errors

Ruflo parses a V3Config object when starting a swarm. The validator checks the swarm topology and memory backend against whitelisted values. Supplying a value outside these sets throws an error and aborts the command.

Topology and Memory Backend Validation

The validation logic lives in v3/src/infrastructure/mcp/tools/ConfigTools.ts. The topology check is performed on lines 59‑62 and the memory backend check on lines 67‑70.

If you see an error such as:

Invalid swarm.topology: circular. Must be one of: hierarchical, mesh, simple, adaptive

or:

Invalid memory.backend: redis. Must be one of: hybrid, agentdb, sqlite

It means the config file contains a typo or an unsupported option. Correct the value or upgrade Ruflo to a version that supports the desired setting.

Task-Level Failures

Each Ruflo task is an instance of the Task class (v3/src/task-execution/domain/Task.ts). The fail method records the error message in the task’s metadata. If a task throws an exception during execution, Ruflo catches it, aggregates it into an Error[], and marks the task as failed (see WorkflowEngine.ts lines 154‑162 and 272‑274).

Common symptoms include “Task failed” messages in the CLI output or a missing error field in the task result payload. The root cause is usually an uncaught exception inside a worker agent (e.g., a syntax error, missing environment variable, or a network timeout). Review the agent’s logs for the original stack trace.

Agent Status Problems

Agents are modeled by the Agent class (v3/src/agent-lifecycle/domain/Agent.ts). Before an agent can accept a request it must be in an active state. If the agent is idle, busy, terminated, or already in error, Ruflo returns a clear error message (see line 48).

Typical triggers include attempting to spawn an agent with a duplicate ID, trying to use an agent after the swarm has been shut down, or a previous task leaving the agent in a hung state. To resolve this, restart the swarm (ruflo swarm stop && ruflo swarm start) or explicitly reset the agent’s status via the MCP agent_reset tool.

Plugin Execution Errors

Ruflo’s extensibility hinges on plugins loaded at runtime (v3/src/infrastructure/plugins/PluginManager.ts). When a plugin handler throws, Ruflo captures the error, records it in the result, and continues loading remaining plugins (see lines 185‑188).

If a plugin crashes, you’ll see messages like “plugin:error” in the event stream. Common causes include missing peer dependencies in the plugin’s package.json or version mismatches between Ruflo core and the plugin’s API. Upgrade the plugin to the latest version or adjust its package.json to match Ruflo’s dependency range.

MCP Tool Dispatch Failures

All MCP‑exposed tools (memory, config, agent, etc.) return a MCPToolResult. If a tool name is unknown, the dispatcher emits an error (see ConfigTools.ts line 117, MemoryTools.ts line 120, and AgentTools.ts line 93).

This typically happens when a CLI wrapper passes a typo (--tool memroy) or a custom script uses an outdated tool name after Ruflo’s API change. Update the tool name to the current schema (memory_search, agent_spawn, etc.) or run ruflo mcp list to view available commands.

Swarm Coordination Edge Cases

The SwarmCoordinator orchestrates task dispatch to agents. It can emit errors when an agent cannot be found or when a task ID is missing (see lines 199 and 254).

These arise when a user references an agent ID that was never spawned or the workflow attempts to cancel a task after it has already completed. Ensure agents are spawned before task submission and guard cancellation calls with a status check.

Practical Solutions and Code Examples

Proper Swarm Initialization

import { swarm_init } from '@claude-flow/mcp';

// Correctly set topology and memory backend
await swarm_init({
  topology: 'hierarchical',
  maxAgents: 8,
  memory: { backend: 'hybrid' },
});

The config passes validation because 'hierarchical' and 'hybrid' are whitelisted values (see ConfigTools.ts validation logic).

Graceful Task Failure Handling

import { runTask } from '@ruflo/v3';

try {
  const result = await runTask('implement-auth');
  if (result.status === 'failed') {
    console.error('Task failed:', result.errors?.[0]?.message);
    // Optional: trigger a rollback or retry
  } else {
    console.log('Task succeeded');
  }
} catch (e) {
  console.error('Unexpected error:', e);
}

The runTask wrapper inspects the Task instance’s fail method (see Task.ts).

Restarting a Stuck Agent

# Stop the swarm (clears all agent states)

ruflo swarm stop

# Start a fresh swarm with the same config

ruflo swarm start --config ./ruflo.config.json

This resets any agents left in an error state (see Agent.ts error handling).

Loading a Plugin Safely

import { loadPlugin } from '@ruflo/plugin-manager';

try {
  await loadPlugin('test-intelligence');
  console.log('Plugin loaded');
} catch (e) {
  console.error('Plugin load failed:', e.message);
}

Any exception inside the plugin is caught and logged (see PluginManager.ts).

Using MCP Memory Tools Correctly

# Store a pattern

ruflo memory store --key "auth‑jwt‑refresh" --value "Refresh token flow" --namespace patterns

# Retrieve it later

ruflo memory retrieve --key "auth‑jwt‑refresh" --namespace patterns

Using the exact tool names avoids the “Unknown tool” guard (see MemoryTools.ts).

Summary

• Configuration Validation: Ruflo enforces whitelisted values for topology and memory.backend in ConfigTools.ts; invalid values abort startup immediately.
• Task Failures: The Task class captures errors via its fail method, while WorkflowEngine.ts aggregates exceptions into error arrays.
• Agent Status: Agents must be in an active state to accept work; duplicate IDs or terminated agents trigger errors from Agent.ts.
• Plugin Errors: PluginManager.ts catches handler exceptions during runtime loading, allowing the system to continue with remaining plugins.
• MCP Tool Dispatch: Unknown tool names trigger guards in ConfigTools.ts, MemoryTools.ts, and AgentTools.ts; use ruflo mcp list to verify available commands.
• Swarm Coordination: SwarmCoordinator.ts emits errors for missing agents or invalid task IDs during dispatch operations.

Frequently Asked Questions

What causes the "Invalid swarm.topology" error in Ruflo?

This error occurs when the V3Config object contains a topology value not present in the whitelist. According to the validation logic in v3/src/infrastructure/mcp/tools/ConfigTools.ts (lines 59‑62), only hierarchical, mesh, simple, and adaptive are valid options. Check your configuration file for typos like circular instead of hierarchical, or upgrade Ruflo if you require a newer topology type.

How does Ruflo handle task execution failures?

Ruflo handles task failures through the Task class in v3/src/task-execution/domain/Task.ts. When a task encounters an exception, the fail method (lines 75‑80) records the error message in the task’s metadata. The WorkflowEngine.ts (lines 154‑162 and 272‑274) catches these exceptions, aggregates them into an Error[] array, and marks the task status as failed. You can inspect the result.errors array in your application code to retrieve specific failure messages.

Why does my Ruflo agent return a status error?

Agent status errors originate from v3/src/agent-lifecycle/domain/Agent.ts (line 48), where the system verifies that an agent is in the active state before accepting requests. If you encounter this error, the agent is likely in idle, busy, terminated, or error state. Common causes include attempting to reuse an agent ID that already exists, calling an agent after the swarm has shut down, or a previous task leaving the agent in a hung state. Resolve this by restarting the swarm with ruflo swarm stop && ruflo swarm start or using the agent_reset MCP tool.

{
  "mcpServers": {
    "instagit": {
      "command": "npx",
      "args": ["-y", "instagit@latest"]
    }
  }
}