Droid Control logo

Droid Control

Organization
Factory-AI
droid-control

Control terminal TUIs, browsers, and native desktop apps for testing, demos, QA, and computer-use tasks. Use when you need to operate an app, automate a CLI, record a demo, or capture proof.

Overview

PublisherFactory-AI
Repositoryfactory-plugins
Skill namedroid-control
Stars
111
Forks
15
Bundled files
Instructions only
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.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by Factory-AI on GitHub. Read the source before you install it.

Installation

Install the Droid Control 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/Factory-AI/factory-plugins.git /tmp/factory-plugins
mkdir -p .claude/skills
cp -r /tmp/factory-plugins/plugins/droid-control/skills/droid-control .claude/skills/droid-control
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Droid Control 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 Droid Control 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 Droid Control 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.

Droid Control

Automate terminals, browsers, and desktop apps. Route by the user's requested method first, then load only the mechanics and evidence stages needed.

Ground rules

  1. Real apps, real environments. Non-deterministic behavior (LLM responses, network latency, variable output) is expected. Handle it with wait / wait-idle. Never substitute fixtures or mocked data.
  2. Recover from evidence. After a failed or uncertain action, observe current state before retrying. Honor method constraints and permission boundaries; a refusal does not authorize another driver or broader target.
  3. Atoms include their references. Load linked material on demand. Desktop-use does not require a separately installed cua skill.
  4. tctl owns recorded terminal sessions. It wraps asciinema rec around the PTY; browser and desktop drivers own their separate lifecycles. Never call tuistory launch directly. Resolve TCTL to an absolute path only for terminal workflows or worker handoffs.
  5. Isolate every run. Multiple droids may be filming simultaneously on the same machine. Session names and output paths share a global namespace (/tmp/tctl-sessions/). At the start of every workflow, generate a run ID (RUN_ID=$(date +%s)-$$ or similar) and use it as a prefix for all session names and a scoped temp directory for all output files:
    bash
    RUN_ID="$(date +%s)-$$"
    RUN_DIR="$(mktemp -d /tmp/droid-run-${RUN_ID}-XXXXXX)"
    # Session names: -s ${RUN_ID}-before, -s ${RUN_ID}-after
    # Output paths: ${RUN_DIR}/before.cast, ${RUN_DIR}/after.cast
    Never use bare session names like -s demo, -s before, -s after — they will collide with concurrent runs. Separate names and paths do not isolate shared desktop focus or keyboard input. Keep one controller for a visible desktop.

Routing

Three independent lookups. Do all three, then load the union of skills they produce.

1. Target route — what are you driving?

TargetLoad these skills
User explicitly requests cua-only, native GUI input, or desktop control (including Electron)desktop-use; method constraints override the defaults below
Droid CLI (droid-dev, droid exec)terminal-use + droid-cli
Other terminal TUIterminal-use
Web page or Electron appbrowser-use
Native desktop GUI appdesktop-use
Raw terminal byte sequencesterminal-use + pty-capture

terminal-use selects the terminal backend behind ${DROID_PLUGIN_ROOT}/bin/tctl: tuistory by default, and it loads true-input when real terminal rendering or keyboard-encoding evidence is needed. Desktop-use includes compositor-specific guidance; inspect live Cua capabilities rather than assuming all Linux targets are X11-only or abandoning the user's chosen method.

2. Stage route — what does the workflow need?

Every workflow passes through stages. Load the atoms for each stage you'll use.

StageSkillWhen to load
CapturecaptureRecording, scripted multi-step evidence, or a demo/QA deliverable; ordinary desktop operation uses the driver's observe/verify loop
ComposecomposeWhen the deliverable is a produced artifact (video, annotated screenshots, comparison image)
VerifyverifyFormal proof, demo, or QA deliverable; every action still needs verification even without this stage

3. Artifact route — does compose need polish tools?

Only relevant when compose is loaded.

Artifact needAlso load
Showcase polish (window chrome, branded frame, cinematic background)showcase
Effects and keystroke overlays(compose handles this — they're fields in the Remotion props JSON)

Workflow shape

Command (intent + commitments)
  → Target route (load driver atoms)
  → Capture (record / screenshot / byte-capture)
  → Compose (assemble deliverable, if needed)
  → Verify (check against commitments)
  → Report

Commands declare what to produce. Atoms own how.

Layout default

Default: single. One clip showing the target/final state. Pick this unless the deliverable is fundamentally a comparison.

CaseLayout
Brand-new feature (no meaningful prior state)single
Bug fix, single-clip proof of the working pathsingle
Walkthrough / tutorial / readme herosingle
Regression proof (broken vs fixed)side-by-side
Behavior-preserving refactor (visual parity is the point)side-by-side
User explicitly asks for a comparisonside-by-side

Do not synthesize a "before" state to justify side-by-side. If there is no real baseline, use single.

Delegation

Keep short interactive desktop tasks in the parent: it owns observations, input, user permission waits, and cleanup. Delegate independent capture environments or rendering, not individual screenshots interleaved with another controller's input.

What to delegate

TaskDelegate?Why
Interactive shared desktopNO — parentOne controller owns focus, snapshots, input, permission waits, and cleanup
Capture clip in an isolated terminal/browser environmentYESWorker owns the complete interaction and recording lifecycle
Capture both clips (comparison layout)YES, only with independent environmentsWorktrees and session labels alone do not isolate a desktop
Remotion renderYESNeeds only props JSON, clip paths, output path. Runs render-showcase.sh (handles .cast conversion, per-render staging, fidelity profiles, longest-clip duration, cleanup)
Planning, interaction scriptingNO — parentRequires PR context and editorial judgment
Layout and prop constructionNO — parentRequires editorial decisions about effects, timing, labels
VerificationNO — parentRequires commitment context
Single ffprobe / file-existence checkNO — inlineToo trivial for subagent overhead

How to delegate

Step 0: Resolve paths and generate a run ID. Workers don't inherit ${DROID_PLUGIN_ROOT}. Resolve once, paste everywhere:

bash
TCTL="$(realpath "${DROID_PLUGIN_ROOT}/bin/tctl")"
RENDER="$(realpath "${DROID_PLUGIN_ROOT}/scripts/render-showcase.sh")"
RUN_ID="$(date +%s)-$$"
RUN_DIR="$(mktemp -d /tmp/droid-run-${RUN_ID}-XXXXXX)"

Use ${RUN_DIR} for all output files (recordings, props, rendered video). Use ${RUN_ID}- as a prefix for all session names. Never use bare names like -s before or hardcoded paths like /tmp/before.cast.

Give workers exact commands with the resolved absolute paths — not abstract instructions, not tuistory, not ${DROID_PLUGIN_ROOT}. The parent does the thinking; the worker executes:

Task prompt for a capture worker:
  "Run these commands in order. Report the output file path and any errors.
   1. /abs/path/to/bin/tctl launch "droid-dev" -s 1712345678-42-before --backend tuistory \
        --repo-root /abs/path/to/baseline/worktree \
        --cols 120 --rows 36 --record /tmp/droid-run-1712345678-42-xxxx/before.cast \
        --env FORCE_COLOR=3 --env COLORTERM=truecolor
   2. /abs/path/to/bin/tctl -s 1712345678-42-before wait ">" --timeout 15000
   3. /abs/path/to/bin/tctl -s 1712345678-42-before type "hello world"
   4. /abs/path/to/bin/tctl -s 1712345678-42-before press enter
   5. /abs/path/to/bin/tctl -s 1712345678-42-before wait-idle
   6. /abs/path/to/bin/tctl -s 1712345678-42-before close"
Task prompt for a Remotion render worker:
  "Run this command. Report the output file path and any errors.
   /abs/path/to/scripts/render-showcase.sh \
     --props /tmp/droid-run-1712345678-42-xxxx/showcase-props.json \
     --output /tmp/droid-run-1712345678-42-xxxx/demo.mp4 \
     /tmp/droid-run-1712345678-42-xxxx/before.cast /tmp/droid-run-1712345678-42-xxxx/after.cast"

Parallel capture pattern (comparison flows only)

Only applicable when the Layout default table selects side-by-side and the capture environments are independent. Serialize shared-desktop captures. For a single interactive desktop task, keep control in the parent.

For before/after comparison demos, launch both capture workers simultaneously:

1. Parent constructs the interaction script (identical for both branches)
2. Launch worker A: capture the baseline/reference branch with `--repo-root` set to that worktree
3. Launch worker B: capture the candidate/change branch with `--repo-root` set to that worktree
4. Wait for both to complete (TaskOutput)
5. Collect .cast paths from results
6. Continue to compose

Shared tooling

Terminal drivers use the unified tctl wrapper. Browser-use and desktop-use have their own CLIs (agent-browser, cua-driver) and do not use tctl.

Drivers can be combined in one workflow — e.g., tctl for a CLI and agent-browser for a web UI it interacts with.

Degraded-tail repro recipe (droid TUI)

Deterministic recipe for reproducing degraded transcript tails in the droid CLI — stranded live tool rows and queued steering messages — without waiting for a slow model turn. The trick: a slow PreToolUse hook pins a tool in its executing state for as long as you need.

  1. Scratch project. Create a throwaway directory (never a real repo — the hook fires on every matching tool call) with a project-local hook that sleeps:

    bash
    SCRATCH="$(mktemp -d /tmp/degraded-tail-XXXXXX)"
    mkdir -p "$SCRATCH/.factory"
    cat > "$SCRATCH/.factory/settings.json" <<'JSON'
    {
      "hooks": {
        "PreToolUse": [
          {
            "matcher": "TodoWrite",
            "hooks": [{ "type": "command", "command": "sleep 120" }]
          }
        ]
      }
    }
    JSON

    Pick a sleep long enough to interact mid-hook (60–180s) and a matcher for a tool the prompt will reliably trigger (TodoWrite fires on any multi-step ask).

  2. Launch with --cwd pointed at the scratch project--repo-root stays on your dev worktree so droid-dev provenance still records the code under test:

    bash
    $TCTL launch "droid-dev" -s ${RUN_ID}-tail --cwd "$SCRATCH" \
      --repo-root /abs/path/to/dev/worktree --record ${RUN_DIR}/tail.cast
  3. Trigger the hook, then degrade the tail while the tool row shows executing:

    • Interrupt mid-hook (press escape) — strands the live tool row: it never resolves to a completed/canceled state in the transcript tail.
    • Steer mid-hook (type "..." + press enter) — the steering message queues behind the executing tool instead of interleaving.

Gotcha: dev-scope hook settings can silently disable project hooks. If the tool completes instantly, run /hooks in the session and check the "Hooks enabled" toggle before debugging the hook config itself.

Prerequisites

StagePlatformRequiredOptional
terminal-use (tuistory)Alltuistory, asciinema, aggtmux
true-inputLinux/Waylandcage, wtype, Wayland terminal, /dev/dri/*grim, wf-recorder
true-inputWindows (KVM)libvirt, qemu, KVM VM with SPICE + SSH, DROID_VM_* env varsvirt-manager
true-inputmacOS (QEMU)qemu, socat, macOS VM with SSH, DROID_MAC_* env vars
browser-useAllagent-browser (+ agent-browser install)
desktop-useAllcua-driver in the intended graphical session; approved OS permissionsDocumentation is bundled; no separate skill install
composeAllffmpeg, ffprobe, agg
showcaseAllNode.js (>= 18), Chrome/Chromium

Install commands

bash
# tuistory driver + recording
npm install -g tuistory                              # virtual PTY driver
pip install asciinema                                # terminal recording (tctl wraps this)
cargo install --git https://github.com/asciinema/agg  # .cast -> .gif converter (compose needs this)

# true-input driver (Linux/Wayland)
sudo apt-get install -y cage wtype                   # required: headless compositor + keystroke injection
sudo apt-get install -y grim wf-recorder             # optional: screenshots + video recording

# agent-browser driver
agent-browser install                                # one-time: downloads bundled Chromium

# desktop-use: follow its setup instructions only if the binary
# is missing and installation is approved. No separate skill install.

# compose + showcase (video rendering)
sudo apt-get install -y ffmpeg                       # video processing (includes ffprobe)
cd ${DROID_PLUGIN_ROOT}/remotion && npm install       # Remotion dependencies
# Chrome or Chromium must be installed for Remotion rendering

Frequently asked questions

What does the Droid Control AI skill do?

Control terminal TUIs, browsers, and native desktop apps for testing, demos, QA, and computer-use tasks. Use when you need to operate an app, automate a CLI, record a demo, or capture proof.

Why use Droid Control on TypingMind?

Because you install it once and use it with any model. Droid Control 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 Droid Control in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Factory-AI/factory-plugins/tree/master/plugins/droid-control/skills/droid-control. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Droid Control?

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 Droid Control?

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

Is the Droid Control AI skill free?

It is published on GitHub by Factory-AI. Check the repository for licensing terms. 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.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇