1password
FreeSet up and use 1Password CLI (op). Use when installing the CLI, enabling desktop app integration, signing in, and reading/injecting secrets for commands.
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Remote-control tmux sessions for interactive CLIs by sending keystrokes and scraping pane output.
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See how to installReview the instructions the agent will receive before you install.
Use tmux only when you need an interactive TTY. Prefer exec background mode for long-running, non-interactive tasks.
SOCKET_DIR="${NANOBOT_TMUX_SOCKET_DIR:-${TMPDIR:-/tmp}/vikingbot-tmux-sockets}"
mkdir -p "$SOCKET_DIR"
SOCKET="$SOCKET_DIR/vikingbot.sock"
SESSION=vikingbot-python
tmux -S "$SOCKET" new -d -s "$SESSION" -n shell
tmux -S "$SOCKET" send-keys -t "$SESSION":0.0 -- 'PYTHON_BASIC_REPL=1 python3 -q' Enter
tmux -S "$SOCKET" capture-pane -p -J -t "$SESSION":0.0 -S -200
After starting a session, always print monitor commands:
To monitor:
tmux -S "$SOCKET" attach -t "$SESSION"
tmux -S "$SOCKET" capture-pane -p -J -t "$SESSION":0.0 -S -200
NANOBOT_TMUX_SOCKET_DIR environment variable."$NANOBOT_TMUX_SOCKET_DIR/vikingbot.sock".session:window.pane (defaults to :0.0).tmux -S "$SOCKET" list-sessions, tmux -S "$SOCKET" list-panes -a.{baseDir}/scripts/find-sessions.sh -S "$SOCKET".{baseDir}/scripts/find-sessions.sh --all (uses NANOBOT_TMUX_SOCKET_DIR).tmux -S "$SOCKET" send-keys -t target -l -- "$cmd".tmux -S "$SOCKET" send-keys -t target C-c.tmux -S "$SOCKET" capture-pane -p -J -t target -S -200.{baseDir}/scripts/wait-for-text.sh -t session:0.0 -p 'pattern'.Ctrl+b d.PYTHON_BASIC_REPL=1 (non-basic REPL breaks send-keys flows).darwin/linux and requires tmux on PATH.tmux excels at running multiple coding agents in parallel:
SOCKET="${TMPDIR:-/tmp}/codex-army.sock"
# Create multiple sessions
for i in 1 2 3 4 5; do
tmux -S "$SOCKET" new-session -d -s "agent-$i"
done
# Launch agents in different workdirs
tmux -S "$SOCKET" send-keys -t agent-1 "cd /tmp/project1 && codex --yolo 'Fix bug X'" Enter
tmux -S "$SOCKET" send-keys -t agent-2 "cd /tmp/project2 && codex --yolo 'Fix bug Y'" Enter
# Poll for completion (check if prompt returned)
for sess in agent-1 agent-2; do
if tmux -S "$SOCKET" capture-pane -p -t "$sess" -S -3 | grep -q "❯"; then
echo "$sess: DONE"
else
echo "$sess: Running..."
fi
done
# Get full output from completed session
tmux -S "$SOCKET" capture-pane -p -t agent-1 -S -500
Tips:
pnpm install first before running codex in fresh clones❯ or $) to detect completion--yolo or --full-auto for non-interactive fixestmux -S "$SOCKET" kill-session -t "$SESSION".tmux -S "$SOCKET" list-sessions -F '#{session_name}' | xargs -r -n1 tmux -S "$SOCKET" kill-session -t.tmux -S "$SOCKET" kill-server.{baseDir}/scripts/wait-for-text.sh polls a pane for a regex (or fixed string) with a timeout.
{baseDir}/scripts/wait-for-text.sh -t session:0.0 -p 'pattern' [-F] [-T 20] [-i 0.5] [-l 2000]
-t/--target pane target (required)-p/--pattern regex to match (required); add -F for fixed string-T timeout seconds (integer, default 15)-i poll interval seconds (default 0.5)-l history lines to search (integer, default 1000)No reviews yet. Tell others what you thought.
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Set up and use 1Password CLI (op). Use when installing the CLI, enabling desktop app integration, signing in, and reading/injecting secrets for commands.
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Use this skill when the user requests to review, analyze, critique, or summarize academic papers, research articles, preprints, or scientific publications. Supports comprehensive structured reviews covering methodology assessment, contribution evaluation, literature positioning, and constructive feedback generation. Trigger on queries involving paper URLs, uploaded PDFs, arXiv links, or requests like "review this paper", "analyze this research", "summarize this study", or "write a peer review".
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Add descriptions for new models from the HuggingFace router to chat-ui configuration. Use when new models are released on the router and need descriptions added to prod.yaml and dev.yaml. Triggers on requests like "add new model descriptions", "update models from router", "sync models", or when explicitly invoking /add-model-descriptions.
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Automates browser interactions for web testing, form filling, screenshots, and data extraction. Use when the user needs to navigate websites, interact with web pages, fill forms, take screenshots, test web applications, or extract information from web pages.
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Master advanced AgentDB features including QUIC synchronization, multi-database management, custom distance metrics, hybrid search, and distributed systems integration. Use when building distributed AI systems, multi-agent coordination, or advanced vector search applications.
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Create and train AI learning plugins with AgentDB's 9 reinforcement learning algorithms. Includes Decision Transformer, Q-Learning, SARSA, Actor-Critic, and more. Use when building self-learning agents, implementing RL, or optimizing agent behavior through experience.
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