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Tmux Agent Comms

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luongnv89
tmux-agent-comms

Manage AI agents in tmux: spawn sessions, send messages, wait, capture replies, inspect fleets, and tear down safely. Use for tmux-hosted CLI agents. Don't use for SSH, GNU screen, or GUI apps.

Overview

Publisherluongnv89
Repositoryskills
Skill nametmux-agent-comms
Stars
124
Forks
18
Bundled files
12
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 12 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by luongnv89 on GitHub. Read the source before you install it.

Installation

Install the Tmux Agent Comms AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/luongnv89/skills.git /tmp/skills
mkdir -p .claude/skills
cp -r /tmp/skills/skills/tmux-agent-comms .claude/skills/tmux-agent-comms
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Tmux Agent Comms in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Tmux Agent Comms on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Tmux Agent Comms is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Tmux Agent Comms

Manage CLI agents in separate tmux sessions. Treat each session as one agent; orchestrate it with send-keys and capture-pane. Relay reply deltas instead of whole screens to protect the context/token budget.

New sessions open in a terminal tab inside the current app by default. If the environment cannot open one, create the session detached and print the exact attach command. Never invoke attach-session from a non-TTY tool.

Use herdr-agent instead when agents live in Herdr.

When to Use

Route directly to the required mode; do not read unrelated references.

TaskStart
Spawn an agentPhase 1
Message or steer an existing agentPhase 2
Read a pane, show status, or inspectPhase 5
Broadcast to a fleetPhase 6
Shut down an agentPhase 6
Main agent's own context is filling upPhase 7 HANDOFF

Prerequisites

  1. Run command -v tmux; stop with installation guidance if it fails.
  2. Resolve helper scripts using references/tmux-recipes.md when messaging, waiting, or broadcasting.
  3. Confirm the exact session and inspect its pane before writing to it.

Critical Rules

  1. Confirm destructive actions. Never send exit//quit, kill a session, or kill the server without explicit approval.
  2. Fail closed before every send. Only preflight exit 0 is sendable; every other code means do not send. Codes are defined once, in the exit-code table (references/delivery-and-waiting.md).
  3. Use a fresh proof cycle. Every message needs a new baseline file and split completion marker. Never reuse either for a follow-up.
  4. Send text and Enter separately. For multiline/code-heavy text, use tmux paste-buffer; see references/tmux-recipes.md.
  5. Bound waiting. Use a wall-clock cap or at most 2–3 re-waits. Surface a stall instead of polling forever.
  6. Keep reads bounded. Start with capture-pane -S -40 and widen only when the reply is truncated.
  7. Escalate blocked panes. A trust/auth/permission dialog requires a human; do not type task text into it.
  8. Run exactly one orchestrator. Only the current main agent writes to fleet sessions. Orchestrator is a role, not a session: after a Phase 7 HANDOFF ack, the outgoing agent goes read-only and issues no further send-keys, spawns, or kills.
  9. Gate your own context. Self-check at every Phase 7 gate point; at or above the threshold, HANDOFF instead of continuing to fill this window.

Workflow

Run Phases 1–6 in order for a send. A read-only status/inspect operation may jump to Phase 5. Phase 7 is the orchestrator's own context gate, evaluated at its named gate points rather than in sequence.

Phase 1 — Create or Discover

List sessions:

bash
tmux list-sessions 2>/dev/null || echo "no tmux server running yet"

Name new sessions <folder>-<short-task> (for example, myrepo-reviewer). Avoid collisions with tmux has-session before creating one. Launch the requested interactive CLI in a new app terminal tab; if no tab facility exists, use detached mode and print tmux attach-session -t <name> for the human.

After spawn, require readiness before assigning work:

bash
python3 "$here/wait_for_idle.py" "$name" --ready --timeout 60 --no-print

Read the result off the exit-code table in references/delivery-and-waiting.md; only exit 0 clears the session for work. Spawn fleets first, then check readiness concurrently. Read references/tmux-recipes.md for naming, tab/detached branches, script resolution, and fleet readiness.

Complete when: every created session has an exact name and passes the ready gate, or the failure is surfaced without sending work.

Phase 2 — Resolve the Exact Target

bash
tmux has-session -t "$target" 2>/dev/null

If missing, list sessions and ask on ambiguity; never guess. Use session:window.pane for a specific pane.

Complete when: one existing tmux target is confirmed.

Phase 3 — Baseline, Preflight, and Send

Read references/delivery-and-waiting.md before sending. Follow its contract:

  1. Capture -S -80 to a temporary baseline file.
  2. Mint a fresh suffix and define completion_marker="TAC_DONE_$suffix".
  3. Append an instruction that prints TAC_DONE_ joined with the suffix only after completion.
  4. Run preflight_send.py immediately before dispatch; send only on exit 0.
  5. Send message text, then send Enter in a separate call.
  6. Check once for post-send activity against the baseline. If unchanged, re-preflight before one recovery Enter; fail if still unchanged.

On multiline/code-heavy input, use paste-buffer rather than shell escaping. Always clean up temporary files on failure.

Complete when: post-send activity proves delivery, or a descriptive failure is surfaced. Typed text alone is not proof.

Phase 4 — Wait and Verify

bash
python3 "$here/wait_for_idle.py" "$target" --timeout 180 --scrollback 80 \
  --baseline-file "$baseline_file" --completion-marker "$completion_marker"
rc=$?
rm -f "$baseline_file"

Handle rc per the exit-code table in references/delivery-and-waiting.md. Before relaying an actionable result, independently compare two short capped-tail captures. Changing output/spinner means working; unchanged output without completion means stalled.

Read references/delivery-and-waiting.md for delivery recovery, wait modes, advisory verdicts, and the anti-deadloop budget.

Complete when: a fresh marker and independent bounded read verify the reply, or the bounded wait ends with an explicit state.

Phase 5 — Read, Status, or Inspect

Read a reply with:

bash
tmux capture-pane -t "$target" -p -S -40

Widen stepwise if capture starts mid-sentence; use unbounded scrollback only as a last resort. Relay substantive lines, not TUI chrome or old turns.

For status, remain read-only and report: agent ID, exact session, state (in-progress, done, blocked, unknown), short progress, start time, and workdir. For inspect, resolve one exact session, include a bounded tail and pane details, then print—but do not run—the human attach command.

Read references/tmux-recipes.md for classification commands, periodic fleet status, scrollback, and troubleshooting.

Complete when: the requested reply or status is concise, target-specific, and not truncated.

Phase 6 — Continue, Broadcast, or Tear Down

  • Continue: restart Phase 3 with a fresh baseline and marker.
  • Broadcast: run "$here/broadcast.sh" "<message>" <session...>; it preflights, sends first, then waits concurrently. Do not serialize send/wait by agent.
  • Long fleet run: emit a read-only status table about every five minutes within the same overall wait budget.
  • Tear down: after explicit confirmation, prefer tmux kill-session -t <name> over tmux kill-server.

Complete when: every follow-up has an independent proof cycle, broadcast failures are reported per target, or confirmed teardown affects only named sessions.

Phase 7 — Hand Off the Orchestrator Role

Long fleet runs outlive one context window. Self-check your own usage at three gate points — before a spawn wave, before a broadcast, and after each relayed capture — never mid-cycle between a send and its wait.

Self-reported usageAction
P >= threshold (default 50, overridable in conversation)HANDOFF
P < thresholdContinue as main
UNKNOWN or unavailableCount relayed reads and spawn waves; HANDOFF at 20 reads or 4 spawn waves

HANDOFF spawns a successor with the same Phase 1 machinery — <folder>-main-g<N>, app terminal tab by default, ready-gated — then delivers a compact handoff brief through the Phase 3 cycle (paste-buffer, since it is multi-line) and waits for the ack HANDOFF ACCEPTED gen=<N> fleet=<k>. After the ack, that session is the orchestrator; this agent goes read-only and prints the successor's tmux attach-session command for the human. A successor that fails readiness or never acks means the HANDOFF failed: stay main, report the unused session, and ask before killing it.

Read references/context-succession.md for the gate-point table, UNKNOWN fallback logging, full procedure, and the brief template. Never paste transcripts or diffs into a brief.

Complete when: the gate decision is recorded with a percentage or an explicit UNKNOWN fallback, and any HANDOFF has a ready successor session, a delivered brief, a received ack, and no write from the outgoing agent afterward.

Acceptance Criteria

  • Every write targets a confirmed session and immediately follows a successful preflight.
  • Every message has a fresh baseline, split marker, delivery check, bounded wait, and independent capped-tail verification.
  • No blocked dialog receives task text; no destructive command runs without confirmation.
  • Fleet sends and readiness checks run concurrently, with partial failures identified by session.
  • The context gate is evaluated at each gate point, and any HANDOFF ends with exactly one acked orchestrator.
  • The expected output is the requested reply/status plus the adapted Step Completion Report below—not raw unbounded scrollback.

Example

bash
target=reviewer
tmux has-session -t "$target" 2>/dev/null || { echo "Error: missing $target" >&2; exit 1; }
# Resolve $here, then follow references/delivery-and-waiting.md for the
# baseline → preflight → send → delivery → wait → verify cycle.

Expected result: the agent's new reply is relayed, the joined marker proves this turn completed, and the report records each gate.

Edge Cases

Eight named conditions — duplicate session name, trust/auth prompt, an undelivered message after the recovery Enter, timeout or stalled pane, follow-up marker reuse, truncated capture, a manually attached human, and a successor that never acks. Read references/reporting-and-edge-cases.md when a phase hits one; do not read it preemptively.

Step Completion Report

Every operation closes with the Step Completion Report block — the requested reply or status plus that block, never raw unbounded scrollback. Emit only the rows the operation actually ran. The block layout, the √ × — ⚠ legend, and the per-operation row table are in references/reporting-and-edge-cases.md.

References

  • references/delivery-and-waiting.md — read for any send/wait cycle, recovery, marker contract, or timeout. Holds the exit-code table, the one definition of every helper exit code.
  • references/context-succession.md — read at the context gate for the HANDOFF procedure and brief template.
  • references/tmux-recipes.md — read only for script resolution, spawn modes, fleets, status/inspect, multiline sends, attach, scrollback, or troubleshooting.
  • references/reporting-and-edge-cases.md — read for the Step Completion Report layout and when an edge case fires.
  • scripts/preflight_send.py — fail-closed check before every send or recovery Enter.
  • scripts/wait_for_idle.py — readiness and settled-reply waiter.
  • scripts/broadcast.sh — safe concurrent fleet broadcast.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Tmux Agent Comms AI skill do?

Manage AI agents in tmux: spawn sessions, send messages, wait, capture replies, inspect fleets, and tear down safely. Use for tmux-hosted CLI agents. Don't use for SSH, GNU screen, or GUI apps.

Why use Tmux Agent Comms on TypingMind?

Because you install it once and use it with any model. Tmux Agent Comms is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Tmux Agent Comms in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/luongnv89/skills/tree/main/skills/tmux-agent-comms. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Tmux Agent Comms?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Tmux Agent Comms?

As many as you like. As long as a model supports skills, you can use Tmux Agent Comms with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Tmux Agent Comms AI skill free?

Yes. It is published on GitHub by luongnv89 under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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