Use when manage multiple local CLI agents via tmux sessions (start/stop/monitor/assign) with cron-friendly scheduling.
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Use when the user wants each agent response to end with a red/yellow/green status line showing whether the work is finished, pending a follow-up, or blocked on input.
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See how to installReview the instructions the agent will receive before you install.
Make completion state obvious at the end of every response.
Every response that completes a unit of work must end with:
🟢 Actual concise status sentence
Rules:
🟢 when the requested work is finished.🟡 when non-routine follow-up remains; name the pending item.🔴 only when blocked on user input.---, spacer lines, or any content after the status line.The convention applies only while this skill is loaded or the user asks for it.
AOS does not inject a managed AGENTS.md / CLAUDE.md block for it.
Choose the status from the user's perspective: finished, pending a specific non-routine step, or blocked.
Finished work:
🟢 Updated quick recap docs with output examples
Non-routine follow-up remains:
🟡 Code updated, set PROVIDER_WEBHOOK_SECRET before testing webhooks
Blocked on user input:
🔴 Need the production API key to continue
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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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