Use when manage multiple local CLI agents via tmux sessions (start/stop/monitor/assign) with cron-friendly scheduling.
中文简介正在准备中。当前显示原文说明。
Use when each agent response should end with a red/yellow/green status line showing whether work is finished, pending follow-up, or blocked.
中文简介正在准备中。当前显示原文说明。
实测评分 未实测
查看安装方法安装前可以查看交给 AI 代理的指令内容。
Make completion state obvious at the end of every response.
For finished work that needs a quick visual summary, build a recap page:
aos-plan-canvas new recap <plan-dir> # scaffold the plan folder
aos-plan-canvas open <plan-dir> --mode bdb-plan-builder # render and open in the browser
aos-plan-canvas await <plan-dir>/plan.mdx # keep listening until the verdict
The approved plan is the artifact: this template has no components, so there is no agenttrail map. The full loop: the plan-canvas skill — a plain CLI, identical on every harness.
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.
中文简介正在准备中。当前显示原文说明。
Use when a hybrid memory system that provides persistent, searchable knowledge management for AI agents (Architecture, Patterns, Decisions).
中文简介正在准备中。当前显示原文说明。
How BDB structures multi-agent build pipelines: the seven-node dispatcher graph /fabric-graph runs. Use for lifecycle framing.
中文简介正在准备中。当前显示原文说明。
Design tools for AI agents. Use when building agent tools: covers schema, error handling, and avoiding hallucination and silent failure.
中文简介正在准备中。当前显示原文说明。
Harness patterns for coding agents — memory, permissions, context engineering, delegation, skills, hooks, bootstrap.
中文简介正在准备中。当前显示原文说明。
agenttrail: the live map of a multi-agent build. Use when a /fabric pipeline runs, a plan-canvas approve lands, or agents run for a human to watch.
中文简介正在准备中。当前显示原文说明。