Use when manage multiple local CLI agents via tmux sessions (start/stop/monitor/assign) with cron-friendly scheduling.
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How to use windows-computer-use-mcp effectively — tool selection, focus rules, safety, and mission design.
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설치 방법 보기설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.
| Goal | Tool | Example |
|---|---|---|
| Click a known button | automation_elements(click, title="Save") | fast, needs exact title |
| Click by intent | automation_smart(click="the Save button") | slower, finds across all windows |
| Complex multi-step | automation_mission(run="save file as PDF") | autonomous loop with retry |
| Record + replay | automation_macro(record) → stop → replay | repeatable sequences |
| Wait for event | automation_watch(start, "window_appears", "Update") | event-driven triggers |
| Explore desktop | automation_smart(discover) | get all running apps |
| Extract + chain | automation_mission(workflow, actions, store_as, dollar-ref) | cross-app data pipeline |
For run operation: provide a clear, concrete goal. The server decomposes via LLM sampling.
For workflow operation: provide explicit steps with tool, params, label, and optional store_as/dollar-ref for data chaining.
For self-healing: set app_path on steps so the mission can re-launch crashed apps.
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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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