Cross-agent shared memory and workflows with open-source Beacon

To solve the friction of repeatedly explaining tasks when switching between coding agents, developers open-sourced Beacon. It hooks into over 20 agent frameworks to capture session telemetry and distills it into reusable workflows for subsequent agents.

Hacker Newsshakshukan

Claude CodeCodexCursorBeaconMCP

Added 2026-10-31 · originally published 2026-10-21

Steps

1Visit the open-source repository to get the Beacon tool: https://github.com/Asymptote-Labs/agent-beacon
2Hook Beacon into the multiple agent frameworks you use (supporting 20+ types)
3As agents run, Beacon captures and standardizes session telemetry such as prompts, tool calls, and command executions
4Use a human review step to distill the captured data into common patterns and repeatable workflows
5Expose the accumulated knowledge via skills or MCP (Model Context Protocol) for any subsequent AI agent to access

Ideas for Chinese platforms

You can apply this approach to multi-platform content operations, distilling viral copywriting frameworks and topic selection rules tested in ChatGPT or Claude into standardized prompt templates for distribution across different writing agents.

Copy-ready prompt

Please review the following historical session data and common error patterns from multiple AI agents: [Enter or paste session telemetry data here]. Help me distill this into a standardized workflow, including common task steps, frequent error patterns, and avoidance strategies, so it can be directly reused later in [Enter target agent name here].

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#AI Agent#Open Source Tools#Workflow Automation#MCP

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Steps

Ideas for Chinese platforms

Related use cases