Use when manage multiple local CLI agents via tmux sessions (start/stop/monitor/assign) with cron-friendly scheduling.
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Draft a client offer with line items priced only from your price list, and send it only after your GO. Use for "write an offer", "quote for this client", "draft a quote", "price this job".
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설치 방법 보기설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.
What you get: a client offer with line items, priced only from your price list.
./pb-offer-<date>/run-log.md — the files are readableno price, never priced by guessoffer.md: items, quantity, unit price, line total, net total, VAT at the rate you gave, gross total, validity — every unit price exists in the price list; the net total recomputed from the line items matchesoffer.md → the cover text at the top of offer.md; no claims beyond the briefoffer.md in full and apply your edits until you approve — approval logged? blocks sending until you fill it) and the full text first. The run stops here until the human types GO. The GO covers exactly the recipient and message shown and nothing else; a different or added recipient needs a fresh GO. The go-gate hook does not guard sending: this [GO] is the only guard.Run log: run-log.md in the save folder. One line per step as it completes (N. done|skipped|failed — file — check result), and WAITING FOR GO: <step> at the gate. Anything other than the literal GO (case-insensitive) is not a GO. 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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