Use when manage multiple local CLI agents via tmux sessions (start/stop/monitor/assign) with cron-friendly scheduling.
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Split one big task into chunks of at most 25 minutes, each with a done-check, and place the demanding ones in your high-energy hours. Use for "split this task", "break it into chunks", "I can't start this", "focus plan". Nothing leaves your computer.
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查看安装方法安装前可以查看交给 AI 代理的指令内容。
What you get: one big task split into 25-minute chunks, ordered by your energy level, each with a done-check.
./pb-focus-chunks-<date>/run-log.md — all answeredchunks.md: numbered chunks of at most 25 minutes, each with minutes, a done-check and an energy tag (high / low) — every chunk is <= 25 min and has a done-check; the minutes add up to your estimatechunks.md so high-energy chunks fall into your high-energy slots and low-energy chunks into the rest → slot named per chunk — no high-energy chunk sits in a low slotchunks.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 writes into the save folder.
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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