用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
直接命令不会经过审查 Prompt;运行前请先检查来源。
npx skills add https://github.com/duclm1x1/Dive-Ai --skill zellij命令会保持在同一行。复制前请横向滚动并检查完整内容。
想先保存到本地?可下载 SkillsMP 当前能够提供的文件。
基于 SOC 职业分类
Persistent memory system for AI agents following Model Context Protocol (MCP). Use for storing long-term memories across sessions, semantic search of past knowledge, building knowledge graphs, auto-injecting context, deduplicating memories, syncing to cloud storage. Essential for agents that need to remember decisions, solutions, preferences, and learned patterns over time.
Persistent memory system for AI agents following Model Context Protocol (MCP). Use for storing long-term memories across sessions, semantic search of past knowledge, building knowledge graphs, auto-injecting context, deduplicating memories, syncing to cloud storage. Essential for agents that need to remember decisions, solutions, preferences, and learned patterns over time.
Master REST and GraphQL API design principles to build intuitive, scalable, and maintainable APIs that delight developers. Use when designing new APIs, reviewing API specifications, or establishing API design standards.
正在显示 SKILL.md
| name | zellij |
| description | Remote-control zellij sessions for interactive CLIs by sending keystrokes and scraping pane output. |
| homepage | https://zellij.dev |
| metadata | {"moltbot":{"emoji":"🪟","os":["darwin","linux"],"requires":{"bins":["zellij","jq"]},"install":[{"id":"brew","kind":"brew","formula":"zellij","bins":["zellij"],"label":"Install Zellij (brew)"},{"id":"cargo","kind":"cargo","crate":"zellij","bins":["zellij"],"label":"Install Zellij (Cargo)"}]}} |
Use zellij only when you need an interactive TTY. Prefer exec background mode for long-running, non-interactive tasks.
DATA_DIR="${CLAWDBOT_ZELLIJ_DATA_DIR:-${TMPDIR:-/tmp}/moltbot-zellij-data}"
mkdir -p "$DATA_DIR"
SESSION=moltbot-python
zellij --data-dir "$DATA_DIR" new-session --session "$SESSION" --layout "default" --detach
zellij --data-dir "$DATA_DIR" run --session "$SESSION" --name repl -- python3 -q
zellij --data-dir "$DATA_DIR" pipe --session "$SESSION" --pane-id 0
After starting a session, always print monitor commands:
To monitor:
zellij --data-dir "$DATA_DIR" attach --session "$SESSION"
zellij --data-dir "$DATA_DIR" pipe --session "$SESSION" --pane-id 0
CLAWDBOT_ZELLIJ_DATA_DIR (default ${TMPDIR:-/tmp}/moltbot-zellij-data).pane-id (numeric) to target specific panes.zellij --data-dir "$DATA_DIR" list-sessions --long or use list-panes.sh.zellij --data-dir "$DATA_DIR" list-sessions.{baseDir}/scripts/find-sessions.sh --all (uses CLAWDBOT_ZELLIJ_DATA_DIR).zellij action to send keystrokes: zellij --data-dir "$DATA_DIR" action --session "$SESSION" write-chars --chars "$cmd".zellij --data-dir "$DATA_DIR" action --session "$SESSION" write 2 (Ctrl+C).zellij --data-dir "$DATA_DIR" pipe --session "$SESSION" --pane-id 0.{baseDir}/scripts/wait-for-text.sh -s "$SESSION" -p 0 -p 'pattern'.Ctrl+p d (zellij default detach).python3 -q.PYTHON_BASIC_REPL=1.darwin/linux and requires zellij on PATH.zellij excels at running multiple coding agents in parallel:
DATA_DIR="${TMPDIR:-/tmp}/codex-army-data"
# Create multiple sessions
for i in 1 2 3 4 5; do
zellij --data-dir "$DATA_DIR" new-session --session "agent-$i" --layout "compact" --detach
done
# Launch agents in different workdirs
zellij --data-dir "$DATA_DIR" action --session "agent-1" write-chars --chars "cd /tmp/project1 && codex --yolo 'Fix bug X'\n"
zellij --data-dir "$DATA_DIR" action --session "agent-2" write-chars --chars "cd /tmp/project2 && codex --yolo 'Fix bug Y'\n"
# Poll for completion (check if prompt returned)
for sess in agent-1 agent-2; do
pane_id=$(zellij --data-dir "$DATA_DIR" list-sessions --long | grep "\"$sess\"" | jq -r '.tabs[0].panes[0].id')
if zellij --data-dir "$DATA_DIR" pipe --session "$sess" --pane-id "$pane_id" | grep -q "❯"; then
echo "$sess: DONE"
else
echo "$sess: Running..."
fi
done
# Get full output from completed session
zellij --data-dir pipe --session --pane-id 0
Tips:
pnpm install first before running codex in fresh clones❯ or $) to detect completion--yolo or --full-auto for non-interactive fixeszellij --data-dir "$DATA_DIR" delete-session --session "$SESSION".{baseDir}/scripts/cleanup-sessions.sh "$DATA_DIR".| Task | tmux | zellij |
|---|---|---|
| List sessions | list-sessions | list-sessions |
| Create session | new-session -d | new-session --detach |
| Attach | attach -t | attach --session |
| Send keys | send-keys | action write-chars |
| Capture pane | capture-pane | pipe |
| Kill session | kill-session | delete-session |
| Detach | Ctrl+b d | Ctrl+p d |
{baseDir}/scripts/wait-for-text.sh polls a pane for a regex (or fixed string) with a timeout.
{baseDir}/scripts/wait-for-text.sh -s session -p pane-id -r 'pattern' [-F] [-T 20] [-i 0.5]
-s/--session session name (required)-p/--pane-id pane ID (required)-r/--pattern regex to match (required); add -F for fixed string-T timeout seconds (integer, default 15)-i poll interval seconds (default 0.5){baseDir}/scripts/find-panes.sh lists panes for a given session.
{baseDir}/scripts/find-panes.sh -s session [-d data-dir]
-s/--session session name (required)-d/--data-dir zellij data dir (uses CLAWDBOT_ZELLIJ_DATA_DIR if not specified)