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The author built and open-sourced a telephony layer for AI agents, enabling them to make calls and send texts via a REST API and MCP server, designed to work with frameworks like OpenClaw, Hermes, LangChain, and Claude Code.
A developer discusses building an execution validator for AI agent-generated graphs where nodes interact via inputs and references, seeking advice between using test accounts or graph traversal for validation.
Teacher Yao's open-source yao-meta-skill is a tool for generating, evaluating, and governing reusable AI skills. It is reportedly more user-friendly than the official skill-creator and integrates best practices from multiple models.
A developer built kaeru, an open-source shared memory system for AI agents that allows them to persist context across sessions, share knowledge between different agents and humans, and visualize memory as a 3D galaxy. The tool supports multiple agent frameworks and includes features like time-travel, importance levels, and reasoning trails.
Built a competitive-intel MCP server that returns only sourced data to prevent AI agents from fabricating competitor numbers.
An analysis of why running more than three parallel agents in Claude Code hits a bottleneck, revealing a duty-cycle problem where the developer becomes the primary latency source, and the 'join' process of merging parallel outputs is the biggest time cost.