lindy-reference-architecture
Reference architectures for Lindy AI agent integrations. Use when designing systems, planning multi-agent architectures, or implementing production integration patterns. Trigger with phrases like "lindy architecture", "lindy design", "lindy system design", "lindy patterns", "lindy multi-agent". '
npx skills add jeremylongshore/claude-code-plugins-plus-skills --skill lindy-reference-architecture --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Lindy Reference Architecture ## Overview Production-ready architecture patterns for integrating Lindy AI agents into applications. Covers webhook integration, multi-agent societies, event-driven pipelines, and high-availability patterns. ## Prerequisites - Understanding of Lindy agent model (triggers, actions, skills) - Familiarity with webhook-based architectures - Production requirements defin
What does the lindy-reference-architecture skill do?
Reference architectures for Lindy AI agent integrations. Use when designing systems, planning multi-agent architectures, or implementing production integration patterns. Trigger with phrases like "lindy architecture", "lindy design", "lindy system design", "lindy patterns", "lindy multi-agent". '
How do I install it?
Run `npx skills add jeremylongshore/claude-code-plugins-plus-skills --skill lindy-reference-architecture --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From jeremylongshore/claude-code-plugins-plus-skills, a repository with 2,596 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.
