Agent skill

Tmux Lane Orchestrator

by vincentkoc in vincentkoc/dotskills

Manage one tmux agent lane from its matching ops pane, inspect live pane state and Codex logs on cold start, and produce concise manager summaries for OpenClaw and adjacent project work.

MITAuto-check passed

Install Tmux Lane Orchestrator

skills CLI
$ npx skills add vincentkoc/dotskills --skill tmux-lane-orchestrator -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install vincentkoc/dotskills tmux-lane-orchestrator --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/vincentkoc/dotskills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/tmux-lane-orchestrator .claude/skills/tmux-lane-orchestrator && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
tmux-lane-orchestrator
GitHub stars
108
Token cost
~3.8k tokens
SKILL.md length
1,995 words
Files
6 (incl. scripts, references, assets)
Skills in repo
19
Repo updated
First seen
Licence
MIT

At a glance

Manage one tmux agent lane from its matching ops pane, inspect live pane state and Codex logs on cold start, and produce concise manager summaries for OpenClaw and adjacent project work.

  • Works in 12 steps: Set the manager pane title immediately → Infer manager scope → Run the cold-start snapshot → …
  • SKILL.md covers Purpose, When to use, Workflow and Inputs, plus 4 more sections
  • Runs Python scripts from its folder; calls python3, codex and pnpm

What it does

Tmux Lane Orchestrator is an agent skill from vincentkoc/dotskills. Manage one tmux agent lane from its matching ops pane, inspect live pane state and Codex logs on cold start, and produce concise manager summaries for OpenClaw and adjacent project work.

Its SKILL.md is about 3.8k tokens, which your agent loads only when the skill is triggered. The skill folder holds 9 other files, including scripts, reference files and assets (for example `agents/openai.yaml`, `references/factory-model.md` and `references/openclaw-lane-matrix.md`). Compatibility notes: Requires tmux. Codex log inspection expects local session logs under ~/.codex/sessions.

It works with tmux. The repository describes itself as: 🐙 A curated set of Codex and OpenClaw skills for workflow automation, technical debugging, and agent-assisted development patterns. The licence is MIT.

Example prompts

  • “/tmux-lane-orchestrator”

Requirements

  • Python 3
  • Compatibility (from SKILL.md): Requires tmux. Codex log inspection expects local session logs under ~/.codex/sessions.

Workflow steps

12 steps, taken from the first numbered list in SKILL.md.

  1. Set the manager pane title immediately
  2. Infer manager scope
  3. Run the cold-start snapshot
  4. Read the operator-provided lane map and treat it as the mission source of truth. If IDs are duplicated or missing, call that out as a…
  5. For each worker pane, classify state
  6. Cross-check live panes against Codex logs before summarizing. Pane titles alone are weak evidence; logs often contain the real task…
  7. If the snapshot helper is slow or stale, do not wait on it forever. Fall back to direct tmux capture-pane, focused jq reads of recent…
  8. Summarize in manager style
  9. When asked to intervene, prefer low-risk coordination first
  10. When launching workers into panes
  11. When assigning OpenClaw work to a fresh worker, create or verify the requested gwt worktree first. The worker prompt must name the exact…
  12. When launching a review-first worker

What it can do on your machine

Read from SKILL.md and the folder at commit 8f972aa. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 1 file in scripts/ (Python), which the agent can run.

    Shell commands in SKILL.md call:

    • python3
    • codex
    • pnpm
    • gh
    • ssh

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md. Its commands use pnpm, gh and ssh, which can reach the network depending on how they are called.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

  • Compatibility

    Requires tmux. Codex log inspection expects local session logs under ~/.codex/sessions.

    From compatibility in the SKILL.md frontmatter.

Context cost

Tmux Lane Orchestrator loads about 3.8k tokens when it runs, and up to ~7.4k if it reads all its reference files. Until then it costs about 52 tokens; SKILL.md has 1,995 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~52
When it runs · the whole SKILL.md, loaded when a task matches
~3.8k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~7.4k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from vincentkoc/dotskills at commit 8f972aa, republished under its MIT licence (© vincentkoc). 1,995 words, ~3,839 tokens.

Download SKILL.mdSave it as .claude/skills/tmux-lane-orchestrator/SKILL.md (or your agent's skills folder). This skill also uses 5 other files; get the full folder from GitHub.
name
tmux-lane-orchestrator
description
Manage one tmux agent lane from its matching ops pane, inspect live pane state and Codex logs on cold start, and produce concise manager summaries for OpenClaw and adjacent project work.
compatibility
Requires tmux. Codex log inspection expects local session logs under ~/.codex/sessions.
license
MIT
metadata.source
https://github.com/vincentkoc/dotskills
metadata.version
0.1.8
metadata.spec
agentskills-v1

tmux Lane Orchestrator

Purpose

Act as the manager for one tmux worker lane. Keep visibility over the lane's panes, infer what each worker is doing from tmux and Codex logs, surface blockers, and give the operator short status summaries with concrete next actions.

The manager owns only its lane by default. Current cockpit topology uses odd ops panes as lane managers:

  • ops.1 manages L1.
  • ops.3 manages L2.
  • ops.5 manages L3.

Treat even-numbered ops panes as spare shells unless the operator explicitly assigns them. Do not inspect or steer another lane unless the operator expands scope.

Read references/factory-model.md when setting up or revising lane responsibilities. Read references/openclaw-lane-matrix.md for OpenClaw-specific worker interpretation.

When to use

  • The operator asks to manage, monitor, summarize, restart, or coordinate a tmux lane.
  • A lane manager cold-starts and must reconstruct worker state from live panes and Codex logs.
  • The operator gives a lane map such as L1.1, L1.2, etc. and wants periodic summaries.
  • OpenClaw or adjacent maintainer work is running across tmux panes and needs traffic control.
  • A worker appears stuck, duplicated, idle, or working on a risky external action.
  • A worker or remote pane has started a dev server, preview, web UI, fixture, or browser-test surface that needs to be reachable from the operator's main local machine.

Workflow

  1. Set the manager pane title immediately:
    • tt title "lane<N> orchestrator" if tt exists.
    • otherwise tmux select-pane -T "lane<N> orchestrator".
  2. Infer manager scope:
    • from explicit user input first;
    • otherwise map current odd ops pane to its lane: 1 -> L1, 3 -> L2, 5 -> L3;
    • if no odd-pane mapping exists, stop and ask for lane scope.
  3. Run the cold-start snapshot:
    • python3 skills/tmux-lane-orchestrator/scripts/lane_snapshot.py --lane <N>
    • add --session <name> when not in the active tmux session.
  4. Read the operator-provided lane map and treat it as the mission source of truth. If IDs are duplicated or missing, call that out as a warning instead of silently rewriting it.
  5. For each worker pane, classify state:
    • active-progress: recent output, running command, or current test/log movement.
    • waiting: watching a check, waiting on Testbox/GitHub/CI capacity, or idle by design.
    • blocked: error shown, local setup mismatch, auth failure, merge conflict, missing dependency, or failed check.
    • idle: shell prompt and no assigned mission.
    • unknown: tmux and logs disagree or evidence is too stale.
  6. Cross-check live panes against Codex logs before summarizing. Pane titles alone are weak evidence; logs often contain the real task, branch, Testbox id, run id, and latest failure.
  7. If the snapshot helper is slow or stale, do not wait on it forever. Fall back to direct tmux capture-pane, focused jq reads of recent ~/.codex/sessions/YYYY/MM/DD/*.jsonl, and live GitHub/Testbox checks for the panes that matter.
  8. Summarize in manager style:
    • one line per pane;
    • include current mission, state, evidence, blocker, and next action;
    • keep a separate manager actions line for anything you will do next.
    • after the compact status, add a short manager read when judgment matters: what is healthy, what is lying, and where attention should go.
  9. When asked to intervene, prefer low-risk coordination first:
    • inspect logs and process state;
    • avoid killing processes unless the operator authorizes the exact process/tree;
    • do not start duplicate heavy checks;
    • do not mutate GitHub or worker panes unless explicitly asked.
  10. When launching workers into panes:
  • prefer creating a prompt file, then passing its contents as the Codex initial prompt argument from the target cwd;
  • use codex --dangerously-bypass-approvals-and-sandbox --no-alt-screen "$(cat prompt-file)";
  • do not feed Codex TUI worker prompts through stdin; it can reject stdin as non-terminal after pane launch;
  • default worker jobs to YOLO mode / no sandbox / no approval prompts unless the operator says to use a safer mode;
  • avoid multi-line here-doc paste directly into multiple panes because tmux can interleave input and corrupt both commands;
  • set a useful pane title before launch, then verify cwd, command, first screen, and trust prompts from scrollback;
  • after launch, submit the staged prompt with Enter/CR if Codex has not begun responding; do not leave the prompt sitting in the input area;
  • if Codex asks for directory trust and the target repo is intended, clear that prompt once and record it in the summary.
  1. When assigning OpenClaw work to a fresh worker, create or verify the requested gwt worktree first. The worker prompt must name the exact worktree path, forbid touching the main checkout, forbid pnpm install inside Codex worktrees, require node_modules symlink verification, and route broad validation through Testbox.
  2. When launching a review-first worker:
  • say explicitly that the worker must not edit code unless the operator asks after the review;
  • allow only the external mutations required to prepare the review, usually clone/pull/fetch;
  • require context checks before conclusions: cwd, repo root, branch, status, remote, free disk, repo instructions, README/package metadata, CI, and tests;
  • keep repo-instruction discovery bounded to the target repo and ancestors, not broad sibling scans;
  • if dependencies are missing, verify documented install/test paths in a temp environment outside the checkout and clean it up;
  • for package or CLI repos, check the installed artifact path, not just editable/source-checkout tests; editable installs can hide missing package data;
  • ask for findings first with file/line evidence, commands run, pass/fail results, quick wins, strategic risks, and a ship/hold/fix-first recommendation.
  • when the review finishes, summarize only the top severity, main recommendation, and whether implementation needs a new explicit go-ahead; keep the worker open for follow-up.
  1. When reallocating active work:
  • name exactly which pane is now the sole coordinator for final integration or push;
  • tell superseded panes to finish only their already-running command, then stop/report branch HEAD, check result, and blockers;
  • preserve useful in-flight Testbox or CI evidence, but do not start duplicate broad gates;
  • coordinator must re-verify cwd, branch, status, symlinks, drift, cheap checks, and final rebase before pushing.
  1. When running a multi-job queue:
  • keep a visible queue with job URL/id, assigned pane, worktree, state, and next action;
  • do live metadata before assignment because "merge as-is" can become conflicts, failed checks, or unresolved review comments;
  • batch merge/closure jobs conservatively to avoid rebase churn;
  • each worker prompt must include exact scope, review/comment obligations, merge/closure policy, and final report shape.
  1. When deciding whether to allocate more work:
  • scrape live lane state first;
  • allocate only when there is idle capacity and a concrete next slice;
  • do not allocate just to use empty panes; more workers without a crisp slice creates coordination sludge;
  • if the right next action is waiting for CI/CodeQL/Testbox or one closeout watcher, say that and leave panes idle;
  • when fresh scanners or runners were just added, validate the live result set before assigning fixers. If new analyses report zero results and open alerts are old-profile residue, allocate closeout/dismissal buckets or a watcher, not implementation lanes.
  1. For metric tracking:
  • store baseline and samples in a local TSV or similar lightweight artifact when the operator asks to track progress over time;
  • report absolute counts plus deltas from baseline, not vibes;
  • verify the tracker process is still alive before relying on it, and restart or sample manually if it died;
  • if new automation is opening work while workers close work, call out the slope honestly.
  1. For secrets and repo settings:
  • do not print, quote back, or store secrets in prompt files;
  • prefer setting secrets with gh secret set <NAME> --repo <owner/repo> using stdin from a shell variable, then unset the variable;
  • record only the secret name, repo, and result, never the value;
  • ask for the narrowest required token permissions when the operator asks.
  • after repo/workflow setup, verify the full path: local checks, remote CI, workflow registration, live smoke, and external service permissions;
  • when an external service blocks on namespace/org permission, report the exact error and prefer manual resource creation over widening token permissions;
  • after the operator changes token or external-service permissions, rerun the exact failed workflow/run/SHA first and pull the fresh log. Do not rebuild the whole setup or broaden permissions until the new failure proves a different boundary.
Show full SKILL.md (684 more words)Show less
  1. When broadcasting updates to active workers:
  • send the update to every assigned pane, not only the active pane;
  • if Codex shows "tab to queue message" or similar, queue the message, press Enter/CR, and then verify the update appears in that worker's log;
  • for urgent validation policy changes, ask each worker to report any already-started command and whether it was stopped, completed, or moved to the correct surface;
  • scan processes after the broadcast and stop only the specific disallowed validation commands you own, not the whole worker.
  1. For watch loops:
  • use the operator's requested cadence;
  • keep the job open and keep messages short, like the L2 operator style;
  • stay silent unless a lane needs attention, finishes, blocks, begins risky external mutation, or the operator asks for a floor read;
  • stop or replace old local watch loops before starting a new monitoring mode;
  • track which evidence is fresh vs memory-derived.
  1. When a worker reports broad test or sweep findings:
  • separate confirmed product/plugin defects from harness, fixture, Testbox, sparse-checkout, dependency, and stale-analysis noise;
  • name the evidence that makes each issue real, and say when a suspicious result is not confirmed yet.
  1. For remote preview ports:
  • treat reachability as part of the deliverable, not a nice-to-have afterthought;
  • first identify the remote host, remote port, bind address, owning process, and whether the manager is on the operator's main local machine or inside the remote machine;
  • remember that mosh does not forward TCP ports; use a separate SSH tunnel;
  • from the main local machine, prefer ssh -4 -fN -o ExitOnForwardFailure=yes -o ServerAliveInterval=15 -o ServerAliveCountMax=3 -L 127.0.0.1:<localPort>:127.0.0.1:<remotePort> <host>;
  • from inside the remote machine, use reverse forwarding only when a known main-local SSH target or explicit operator instruction exists; otherwise give the exact main-local forwarding command and mark the tunnel as blocked on main-local access;
  • avoid local port collisions by checking lsof -nP -iTCP:<localPort> -sTCP:LISTEN; if the requested port is occupied, choose the next obvious port and say so;
  • verify the tunnel with lsof and curl before handoff, and report the local URL plus SSH tunnel PID;
  • do not kill existing tunnels unless they were created by the current task or the operator names the PID/scope.
  1. For OpenClaw lanes, apply references/openclaw-lane-matrix.md.
  2. Preserve the lane taxonomy unless the operator overrides it:
  • L1: fixes and maintainer hygiene.
  • L2: feature work.
  • L3: exploratory work.

Inputs

  • lane (required unless inferable): numeric lane id such as 1.
  • tmux_session (optional): tmux session name; default is the current session.
  • mission_map (optional): operator-provided mapping of L<N>.<pane> to mission.
  • snapshot_depth (optional): capture lines per pane; default 80.
  • log_depth (optional): number of recent Codex logs to scan; default 12.
  • mode (optional): observe (default), summarize, intervene, or recover.
  • scope_override (optional): explicit permission to inspect another lane.

Outputs

  • Lane snapshot with panes, cwd, command, pid, active state, and recent output.
  • Codex log hints: session id, cwd, latest user request, recent assistant status, recent tool/check evidence.
  • Worker state table with pane, mission, state, evidence, risk, and next action.
  • Short operator summary suitable for repeated updates.
  • Escalations requiring operator approval, especially process kills, broad test runs, or external mutations.

Cold-Start Rules

  • Ignore saved cockpit layout files unless the operator explicitly asks for them. Use live tmux and current logs.
  • Treat the operator's latest lane map as fresher than memory, pane titles, or old logs.
  • Verify current cwd, git branch/status, and long-running command indicators for any pane before declaring it idle.
  • Search today's Codex logs first, then recent dated logs only if today's logs are insufficient.
  • For log inspection, start with session metadata and user/assistant event messages. Raw tool output is supporting evidence only after a targeted question; dumping tool logs makes the manager slower and noisier.
  • Log evidence is advisory when stale. Prefer live tmux output for current blocking state.
  • Snapshot output may include the manager's own current session when keywords overlap. Ignore self-referential lines unless they explain the active management task.
  • If the manager is recovering after a crash, summarize task, status, pending work, and next step before taking action.

Manager Summary Format

Use this compact shape:

text
lane L<N> status
L<N>.1 <state> - <mission>. evidence: <short proof>. next: <action>.
L<N>.2 <state> - <mission>. evidence: <short proof>. next: <action>.
...
manager actions: <what i will inspect/ask/do next>
risks: <only material blockers or duplicate-work hazards>

Keep it blunt. The operator needs factory-floor signal, not a diary.

Flow

mermaid
stateDiagram-v2
    [*] --> ResolveManagerLane
    ResolveManagerLane --> ReportMissingScope: lane cannot be resolved
    ResolveManagerLane --> CaptureLiveEvidence: exact lane known
    CaptureLiveEvidence --> DirectBoundedInspection: helper slow or stale
    CaptureLiveEvidence --> ClassifyAndSummarize: evidence current
    DirectBoundedInspection --> ClassifyAndSummarize
    ClassifyAndSummarize --> ReportState: observe or summarize
    ClassifyAndSummarize --> InterveneWithinScope: named intervention authorized
    InterveneWithinScope --> VerifyResultAndReachability
    VerifyResultAndReachability --> ReportState
    ReportMissingScope --> [*]
    ReportState --> [*]

© vincentkoc, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 5 other files (scripts, references, assets) in skills/tmux-lane-orchestrator of vincentkoc/dotskills.

  • SKILL.md
  • agents/openai.yaml
  • assets/icon.jpg
  • references/factory-model.md
  • references/openclaw-lane-matrix.md
  • scripts/lane_snapshot.py

Open the folder on GitHubat commit 8f972aa

Compare with similar skills

Tmux Lane Orchestrator next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Tmux Lane Orchestrator compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Tmux Lane Orchestrator this skillvincentkoc/dotskills108—~3.8kAutomated safety check: PassMIT
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CodeGraph Agent Evalcolbymchenry/codegraph74k—~950Automated safety check: PassMIT
Tmuxtrpc-group/trpc-agent-go1.9k23 repos~868Automated safety check: PassApache-2.0
CodexBar Live QAsteipete/CodexBar22k—~1.2kAutomated safety check: PassMIT
Tmuxopenclaw/openclaw392k1 repos~640Automated safety check: PassMIT

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Works with

Questions about Tmux Lane Orchestrator

What does Tmux Lane Orchestrator do?

Manage one tmux agent lane from its matching ops pane, inspect live pane state and Codex logs on cold start, and produce concise manager summaries for OpenClaw and adjacent project work. Tmux Lane Orchestrator is an agent skill from vincentkoc/dotskills. Manage one tmux agent lane from its matching ops pane, inspect live pane state and Codex logs on cold start, and produce concise manager summaries for OpenClaw and adjacent project work.

How do I install Tmux Lane Orchestrator in Claude Code?

Run `npx skills add vincentkoc/dotskills --skill tmux-lane-orchestrator -a claude-code`. Or copy the skill folder (skills/tmux-lane-orchestrator in vincentkoc/dotskills) into .claude/skills/tmux-lane-orchestrator in your project. Claude Code loads it when a task matches its description.

How do I install Tmux Lane Orchestrator in Codex?

Run `npx skills add vincentkoc/dotskills --skill tmux-lane-orchestrator -a codex`. Or copy the skill folder (skills/tmux-lane-orchestrator in vincentkoc/dotskills) into .agents/skills/tmux-lane-orchestrator in your project. Codex loads it when a task matches its description.

Can I use Tmux Lane Orchestrator in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add vincentkoc/dotskills --skill tmux-lane-orchestrator -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/tmux-lane-orchestrator, .gemini/skills/tmux-lane-orchestrator, .github/skills/tmux-lane-orchestrator and .opencode/skills/tmux-lane-orchestrator in your project.

What does Tmux Lane Orchestrator need to run?

Going by SKILL.md and its folder, Tmux Lane Orchestrator needs Python for the scripts in its folder and the command-line tools its instructions call (python3, codex, pnpm, gh and ssh). Our summary lists: Python 3. Compatibility (from SKILL.md): Requires tmux. Codex log inspection expects local session logs under ~/.codex/sessions..

Does Tmux Lane Orchestrator access the network?

SKILL.md contains no URLs. Its commands use gh and ssh, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is Tmux Lane Orchestrator safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Tmux Lane Orchestrator use?

Tmux Lane Orchestrator is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Tmux Lane Orchestrator use?

About 3.8k tokens (SKILL.md is roughly 15k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 3.6k tokens, read only when the agent opens those files.

What are the alternatives to Tmux Lane Orchestrator?

Skills that share tags, products or a category with Tmux Lane Orchestrator: 1password (trpc-group/trpc-agent-go, 1.9k stars), CodeGraph Agent Eval (colbymchenry/codegraph, 74k stars), Tmux (trpc-group/trpc-agent-go, 1.9k stars) and CodexBar Live QA (steipete/CodexBar, 22k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Tmux Lane Orchestrator?

vincentkoc (a GitHub user) maintains it in vincentkoc/dotskills, which has 108 GitHub stars. The repository holds 19 skills in this directory. The repository was last updated on October 8, 2026.

Source: vincentkoc/dotskills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.