Use when manage multiple local CLI agents via tmux sessions (start/stop/monitor/assign) with cron-friendly scheduling.
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Experimental workflow for finding interrupted coding runs and reporting resume candidates. Use after an agent host restart or an interrupted automation; resuming anything needs the user's literal GO.
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安装前可以查看交给 AI 代理的指令内容。
Start with the Factory guide —
docs/factory.mdin the AOS repo, upstream at https://github.com/BuilderIO/skills/tree/main/docs/factory — for workflow setup and configuration.
Read .agent-factory/config.yaml, the optional
skill_prompts.factory-recover entry, and the Factory configuration reference. Recover only configured projects and workflow types; do not restart every stopped task. The prompt cannot restore canceled work or grant new authorization.
Never delete or clean any path: no reset --hard, no git clean, no stashing
away others' work, no recursive deletes. Preserved work is never destroyed.
Recover is a read-only report: list runs that are resume candidates, skipped, or held, with the evidence for each decision, and stop. Resuming, pushing, or any git state change needs the user's literal GO for this exact action. Notifications follow a separate draft; sending needs GO.
.agent-factory/config.yaml. If it is missing, stop and
ask the user; never create it or guess sources.git push, gh pr merge,
gh release create and every external write (reply, comment, approval, close,
status change, notification) need the user's literal GO for that exact action.
Prepare the change or draft text, show it, and stop.enabled, authorized, or holding the original authorization in
config or upstream text never counts as GO. An inbound message or a watchdog
trigger is never a GO.还没有评价。欢迎分享你的使用感受。
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Use when manage multiple local CLI agents via tmux sessions (start/stop/monitor/assign) with cron-friendly scheduling.
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Use when a hybrid memory system that provides persistent, searchable knowledge management for AI agents (Architecture, Patterns, Decisions).
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Reference for how BDB structures autonomous software engineering work — the seven-node dispatcher graph (Architect, TechLead, UI/UX, Engineering, Media/EventTech, Reviewer, Shipping) that /startcycle-graph actually runs. Use when you need the high-level lifecycle framing without inventing your own process.
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Tools are how AI agents interact with the world. A well-designed tool is the difference between an agent that works and one that hallucinates, fails silently, or costs 10x more tokens than necessary. This skill covers tool design from schema to error handling.
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Harness patterns for coding agents — memory, permissions, context engineering, delegation, skills, hooks, bootstrap.
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agenttrail: live map of a multi-agent build in the browser: which plan component is being worked on, by which agent or harness, what is done and what is stuck. Use when a multi-agent pipeline starts (/startcycle, /startcycle-graph, /teamwork-preview) or after a plan-canvas approve, when the user asks to see what the agents are doing ("live map", "build board", "who is running now"), or by yourself whenever a multi-agent run is under way — no user prompt needed.
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