Use when manage multiple local CLI agents via tmux sessions (start/stop/monitor/assign) with cron-friendly scheduling.
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Turn your scattered to-do lists and notes into one prioritised plan for the week, with at most 3 must-do items per day. Use for "plan my week", "what should I do this week", "sort my to-dos", "weekly plan from my notes". Nothing leaves your computer unless you opt in to steps 4 or 8.
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설치 방법 보기설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.
What you get: one prioritised plan for this week, built from your scattered to-do lists and notes.
./pb-week-plan-<date>/run-log.md — the folders existinbox.md, every open item with its source file and line — at least one item, otherwise stop and askinbox.md tagged [memB] — skipped and logged if memB is not installedgh (external) is installed: your own open pull requests → added to inbox.md — your choice recordedcalendar.md with the fixed appointments — skipped if none was giveninbox.md and calendar.md → week-plan.md, per day Must (max 3), Should, Could — every line traces to a line in inbox.md or calendar.md; nothing inventedweek-plan.md in full and apply your edits until you approve — approval loggedNothing in this plan is sent anywhere, so there is no GO step. It only reads the files you named and writes into the save folder, except the opt-in steps 4 (gh queries GitHub) and 8 (writes memB).
Run log: run-log.md in the save folder. One line per step as it completes (N. done|skipped|failed — file — check result). If a check fails, stop, write the failure into the log and tell the user.
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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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