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 to build and deploy a project to a real server via rsync over SSH — "deploy this", "push the build live", "sync to production". Not for git push/PR workflows, and not a replacement for a real CI pipeline; this is the direct-deploy path.
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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。
A thin wrapper around the real bdb-deploy CLI (bin/bdb-deploy.mjs in this package). This skill does not construct rsync/ssh commands itself. The CLI does that deterministically; the skill's job is knowing when and how to invoke it, and reading its output correctly.
Freehand rsync/ssh commands written by an LLM in the moment are a real risk once they touch a production web root or hold an SSH key path: a wrong flag, a missing trailing slash on an rsync source (changes whether the contents or the directory itself gets copied), or a mistyped remote path can silently corrupt or wipe a live deployment. The CLI encodes the correct, tested behavior once; this skill just knows how to call it.
bdb-deploy.json in the project root. If it doesn't exist, this project isn't set up yet — see "First-time setup" below.bdb-deploy.json has no secrets in it, safe to read directly). Note which targets are "production": true.Run bdb-deploy init interactively — it asks the user for host, SSH user, key path, remote directory, etc. Do not pre-fill these from guesses; if you don't know the real values (host, remote path, which SSH key), ask the user rather than inventing plausible-sounding ones. A wrong host or path here means the next command genuinely deploys somewhere unintended.
Always dry-run first unless the user explicitly says to skip it:
bdb-deploy --target <name> --dry-run
Read the dry-run output. It shows the exact build command, the exact rsync source/destination, and the exact remote restart command (if configured) — none of it executes in dry-run mode. Confirm this matches what the user actually wants before proceeding.
Then the real run:
bdb-deploy --target <name>
If the target is marked "production": true, the CLI itself will prompt for confirmation (typing the target name) unless --yes is passed. Do not pass --yes on a production target on the user's behalf unless they've explicitly said to skip confirmation for this specific run — that confirmation prompt exists precisely so a human is in the loop for the highest-consequence targets.
healthcheckUrl is configured, the CLI GETs it after deploy and fails loudly (non-zero exit) if it doesn't respond OK. Trust this over assuming the deploy worked just because rsync didn't error — a successful file copy to the wrong path still "succeeds" at the rsync level..env, then re-run through the CLI..forgejo/workflows/ or .github/workflows/ that already builds and deploys on push), prefer that — don't bypass it with a manual bdb-deploy run unless the user asks to.bdb-deploy.json and .env are per-project and per-machine; this tool makes no assumption about which host, user, or path a project deploys to.还没有评价。欢迎分享你的使用感受。
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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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