What problem does it solve? Building Lark/Feishu bots or automation that reacts to real-time events (incoming messages, reactions, meeting endings, generated minutes, whiteboard edits) normally requires standing up webhook servers and managing subscriptions. This Skill lets an AI agent subscribe to and stream those events directly as NDJSON via lark-cli event consume, with a subprocess contract designed for agent callers. ## Core Features & Use Cases - Event discovery and schema inspection: List all subscribable EventKeys with lark-cli event list and inspect each key's params and output schema with lark-cli event schema before writing jq filters. - Bounded or unbounded consumption: Stream events to stdout as NDJSON, with --max-events / --timeout for bounded runs, --jq for filtering and projection, and a stderr ready-marker plus structured exit codes for reliable subprocess orchestration. - Domain references: Detailed catalogs for 11 IM EventKeys, 2 VC EventKeys, 1 Minutes EventKey, and 1 Whiteboard EventKey, including field semantics, auth scopes, and jq recipes. - Use Case: Build a Lark bot that watches im.message.receive_v1, filters for group text messages mentioning a keyword, and pipes matching events into a downstream summarization pipeline. ## Quick Start Ask the AI to listen for incoming Lark messages by running lark-cli event consume im.message.receive_v1 as the bot identity and show you the streamed events.