Agent skill

Use Appclaw CLI

by appclawhq in appclawhq/AppClaw

Use the AppClaw CLI to run YAML flows, start the interactive TUI shell, explore apps, record/replay sessions, configure devices, and troubleshoot.

Apache-2.0Auto-check: notesMobile

Install Use Appclaw CLI

skills CLI
$ npx skills add appclawhq/AppClaw --skill use-appclaw-cli -a claude-code

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

GitHub CLI
$ gh skill install appclawhq/AppClaw use-appclaw-cli --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/appclawhq/AppClaw.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/use-appclaw-cli .claude/skills/use-appclaw-cli && 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
use-appclaw-cli
GitHub stars
116
Token cost
~4.6k tokens
SKILL.md length
1,459 words
Files
1
Skills in repo
4
Repo updated
First seen
Licence
Apache-2.0

At a glance

Use the AppClaw CLI to run YAML flows, start the interactive TUI shell, explore apps, record/replay sessions, configure devices, and troubleshoot.

  • Works in 7 steps: Agent Mode (default) — LLM-driven… → YAML Flow Mode — declarative, no LLM cost → Terminal Studio (--tui, alias… → …
  • Any request involving appclaw commands
  • SKILL.md covers Prerequisites, Source of Truth, CLI Modes & Commands and Platform & Device Selection, plus 3 more sections
  • Calls npm, adb and xcrun; reaches github.com and generativelanguage.googleapis.com; needs LLM_API_KEY and GEMINI_API_KEY

What it does

Use Appclaw CLI is an agent skill from appclawhq/AppClaw. Use the AppClaw CLI to run YAML flows, start the interactive TUI shell, explore apps, record/replay sessions, configure devices, and troubleshoot. Trigger for any request involving appclaw commands, device setup, .env configuration, running flows, vision setup, or debugging execution failures.

Its SKILL.md is about 4.6k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Mobile, covering Mobile testing and debugging. It works with iOS, Android and Model Context Protocol. The repository describes itself as: AI-powered mobile automation agent — describe what you want in plain English, AppClaw reads the screen, reasons, and acts. LLM-agnostic, open-source, zero telemetry. The licence is Apache-2.0.

When your agent uses it

  • Any request involving appclaw commands
  • .env configuration
  • Debugging execution failures

Example prompts

  • “/use-appclaw-cli”

Requirements

  • Node.js
  • A credential in LLM_API_KEY
  • A credential in GEMINI_API_KEY

Workflow steps

7 steps, taken from the step headings in SKILL.md.

  1. Agent Mode (default) — LLM-driven automation
  2. YAML Flow Mode — declarative, no LLM cost
  3. Terminal Studio (--tui, alias --playground)
  4. Explorer — PRD to test flows
  5. Record & Replay
  6. Report Server
  7. Goal Decomposition

What it can do on your machine

Read from SKILL.md and the folder at commit 9bbc6f1. 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

    Shell commands in SKILL.md call:

    • npm
    • adb
    • xcrun
    • npx
    • git

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

  • Network

    Hosts in commands or code, which the agent is likely to contact:

    • github.com
    • generativelanguage.googleapis.com

    Also links to:

    • ollama.ai

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

  • Credentials

    Names these keys or tokens, usually read from environment variables:

    • LLM_API_KEY
    • GEMINI_API_KEY
    • STARK_VISION_API_KEY
    • AI_VISION_API_KEY

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

Context cost

Use Appclaw CLI loads about 4.6k tokens when it runs. Until then it costs about 78 tokens; SKILL.md has 1,459 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~78
When it runs · the whole SKILL.md, loaded when a task matches
~4.6k

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: notes

The automated check noted patterns worth knowing about, such as sudo or a known installer.

  • NoteMentions a .env fileSKILL.md:6
    nvolving appclaw commands, device setup, .env configuration, running flows, vision
  • NoteMentions a .env fileSKILL.md:53
    - Inspect `.env` for the user's active configuration.
  • NoteMentions a .env fileSKILL.md:90
    **Requires:** `LLM_API_KEY` in `.env` (except Ollama). If it is missing the shell
  • NoteMentions a .env fileSKILL.md:213
    ## Configuration (`.env`)
  • NoteMentions a .env fileSKILL.md:215
    All configuration via `.env` in the working directory. Copy `.env.example` to get started:
  • NoteMentions a .env fileSKILL.md:218
    cp .env.example .env
  • NoteMentions a .env fileSKILL.md:333
    - Reading `.env`, `.appclaw/env/`, flow YAML files
  • NoteMentions a .env fileSKILL.md:389
    PI key required" | Set `LLM_API_KEY` in `.env`

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); files beside SKILL.md are not scanned.

SKILL.md

The full file from appclawhq/AppClaw at commit 9bbc6f1, republished under its Apache-2.0 licence (© appclawhq). 1,459 words, ~4,640 tokens.

Download SKILL.mdSave it as .claude/skills/use-appclaw-cli/SKILL.md (or your agent's skills folder).
name
use-appclaw-cli
description
Use the AppClaw CLI to run YAML flows, start the interactive TUI shell, explore apps, record/replay sessions, configure devices, and troubleshoot. Trigger for any request involving appclaw commands, device setup, .env configuration, running flows, vision setup, or debugging execution failures.

AppClaw CLI Operator

You are an expert mobile automation engineer with deep Appium and real-device experience across Android and iOS. Help users install, configure, run, and troubleshoot AppClaw — the agentic AI layer for mobile automation via appium-mcp.

Prerequisites

AppClaw requires:

  • Node.js 18+
  • A connected device — USB Android, Android emulator, iOS simulator, or real iOS device
  • An LLM API key (except for Ollama which runs locally)
Install
sh
# Global install
npm install -g appclaw

# Or run from a local clone
git clone https://github.com/AppiumTestDistribution/appclaw.git
cd appclaw && npm install
Verify
sh
appclaw --help
appclaw --version

From a local clone, use npm start instead of appclaw:

sh
npm start -- --help
npm start "Open Settings"
npm start -- --flow examples/flows/google-search.yaml

Source of Truth

  • Prefer appclaw --help for current flag reference.
  • Inspect .env for the user's active configuration.
  • Read .appclaw/env/ for variable/secret bindings before giving flow advice.
  • Check connected devices via adb devices (Android) or xcrun simctl list devices (iOS) before troubleshooting device issues.
  • Do not invent unsupported flags or commands.

CLI Modes & Commands

1. Agent Mode (default) — LLM-driven automation
sh
# Resident shell — device picker, then a prompt you can run goal after goal in
appclaw

# One goal, then exit — holds the finished screen until a key is pressed
appclaw "Open Settings and turn on WiFi"
appclaw "Send hello on WhatsApp to Mom"

# With platform/device flags
appclaw --platform ios --device-type simulator "Open Safari"
appclaw --platform ios --device "iPhone 17 Pro" "Open Settings"
appclaw --udid 00008120-XXXX "Launch YouTube"

# Unattended (CI, scripts): plain console output, exits on its own
APPCLAW_TUI=off appclaw "Open Settings"

Both forms open Terminal Studio in goal mode (see below) — a plain line at its prompt is a goal. The exit code is unchanged: 0 when every sub-goal completed, 1 otherwise. --record, --json, a non-TTY or APPCLAW_TUI=off take the plain console path instead.

Add --export [path] to write the finished run out as a replayable @appclaw/runner spec (--export-dir or EXPORT_DIR decides where a bare filename lands; default tests). Inside the shell the same thing is /export.

Requires: LLM_API_KEY in .env (except Ollama). If it is missing the shell says so on a setup screen and offers to write it, rather than exiting.

2. YAML Flow Mode — declarative, no LLM cost
sh
appclaw --flow path/to/flow.yaml
appclaw --flow examples/flows/youtube-search-appium3.yaml
appclaw --flow tests/flows/youtube-phased.yaml --env dev

Flags:

  • --env <name> — select environment file (.appclaw/env/<name>.yaml) for variable/secret resolution

No LLM key needed unless the flow has steps that fall back to LLM parsing (unrecognized natural language).

3. Terminal Studio (--tui, alias --playground)
sh
appclaw --tui
appclaw --tui --platform ios --device-type simulator
appclaw --tui --device "iPhone 17 Pro"

One shell, two modes, decided by what a plain (non-slash) line means:

  • record (--tui) — a plain line is one deterministic instruction, run live on the device and appended to a recording. /list, /yaml, /edit and /export work on that recording.
  • goal (bare appclaw) — a plain line is a goal, run through the full planner. Nothing is recorded; /export writes the run the agent just did.

/mode goal|record switches without dropping the device session, and /goal <text> works in either. The command palette is listed permanently in record mode; in goal mode it stays hidden until the line starts with /.

--playground is an alias for --tui — the old playground REPL was removed. (--json --playground is different: a headless NDJSON bridge used by the VS Code / Cursor extension, not something to run by hand.)

Full-screen Ink shell: platform/device picker, slash-command palette, settings, run history. Device mirroring draws the screen inside the terminal — Kitty graphics on Ghostty/kitty/WezTerm, 24-bit ANSI half-blocks everywhere else — via adb screencap on Android and xcrun simctl io … screenshot on an iOS simulator, inside a drawn device body. Frame rate is device-bound: ~5fps on a fast Android device, ~3fps on a simulator, and as low as ~1fps on a software-rendered emulator. Start it with ^r or /stream, freeze it with ^p, tear it down with ^x; --stream starts it as soon as the session opens, which is the only way to see it during appclaw "a goal". Requires an interactive terminal; incompatible with --json.

4. Explorer — PRD to test flows
sh
appclaw --explore "YouTube app with search and playback" --num-flows 5
appclaw --explore prd.txt --no-crawl --num-flows 3
appclaw --explore "Settings app" --output-dir my-flows --max-screens 15 --max-depth 4
FlagDefaultPurpose
--num-flows <N>5Number of flows to generate
--no-crawlfalseSkip device crawling (PRD-only analysis)
--output-dir <dir>generated-flowsWhere to write generated YAML files
--max-screens <N>10Max screens to crawl
--max-depth <N>3Max navigation depth during crawl
5. Record & Replay
sh
# Record a goal execution (actions saved to logs/)
appclaw --record "Open Settings"

# Replay a recording (adaptive — reads screen, not coordinates)
appclaw --replay logs/recording-xyz.json
6. Report Server
sh
appclaw --report
appclaw --report --report-port 8080

Starts an Express server serving HTML reports from .appclaw/runs/. Default port: 4173.

7. Goal Decomposition
sh
appclaw --plan "Copy the weather and send it on Slack"

Breaks complex multi-app goals into sub-goals, then executes each.


Platform & Device Selection

Priority Order
  1. CLI flags (--platform, --device-type, --udid, --device)
  2. Environment variables (PLATFORM, DEVICE_TYPE, DEVICE_UDID, DEVICE_NAME)
  3. Interactive prompt (TTY only)
Android
sh
# Default — auto-detects connected device
appclaw "Open Settings"

# Specific emulator
appclaw --udid emulator-5554 "Open Settings"

Android requires ANDROID_HOME or ANDROID_SDK_ROOT set (defaults to $HOME/Library/Android/sdk on macOS).

iOS Simulator
sh
appclaw --platform ios --device-type simulator "Open Settings"
appclaw --platform ios --device-type simulator --device "iPhone 17 Pro" "Open Settings"
  • If only one simulator is booted, it's auto-selected.
  • The CLI boots the simulator, downloads WebDriverAgent (cached in ~/.cache/appium-mcp/wda/), and installs WDA automatically.
iOS Real Device
sh
appclaw --platform ios --device-type real --udid 00008120-XXXX "Open Settings"
  • WebDriverAgent must be pre-installed on the device (Xcode signing required).
  • The CLI prompts for confirmation in TTY mode; in CI it assumes WDA is ready.
  • See appium-xcuitest-driver real device setup for WDA signing instructions.

Configuration (.env)

All configuration via .env in the working directory. Copy .env.example to get started:

sh
cp .env.example .env
LLM Setup (required for agent/explorer/planner modes)
VariableDefaultOptions
LLM_PROVIDERanthropicanthropic, openai, gemini, groq, ollama
LLM_API_KEY—Your provider's API key (not needed for Ollama)
LLM_MODELautoOverride model ID (see defaults below)

Default models per provider:

ProviderDefault Model
anthropicclaude-sonnet-4-20250514
openaigpt-4o
geminigemini-2.0-flash
groqllama-3.3-70b-versatile
ollamallama3.2
Agent Mode & Vision

Two strategies for finding elements on screen:

SetupAGENT_MODEBest For
DOM modedomStandard apps with good accessibility labels. Uses XML page source. Works with any LLM.
Vision modevisionCustom views, canvas-rendered UI, games. Screenshot-first with AI vision.
DOM Mode (simplest)
env
LLM_PROVIDER=gemini
LLM_API_KEY=your-key
AGENT_MODE=dom
env
LLM_PROVIDER=gemini
LLM_API_KEY=your-gemini-key
AGENT_MODE=vision
VISION_LOCATE_PROVIDER=stark
GEMINI_API_KEY=your-gemini-key

Stark uses df-vision + Gemini in-process. Same API key works for both LLM and vision.

Vision + appium-mcp
env
LLM_PROVIDER=gemini
LLM_API_KEY=your-key
AGENT_MODE=vision
VISION_LOCATE_PROVIDER=appium_mcp
AI_VISION_ENABLED=true
AI_VISION_API_BASE_URL=https://generativelanguage.googleapis.com/v1beta/openai
AI_VISION_API_KEY=your-key
AI_VISION_MODEL=gemini-2.0-flash
AI_VISION_COORD_TYPE=absolute
Vision Fallback (DOM + Vision hybrid)

Even in DOM mode, vision can kick in when DOM matching fails:

env
AGENT_MODE=dom
VISION_MODE=fallback    # always | fallback | never
Show full SKILL.md (611 more words)Show less
Tuning Parameters
VariableDefaultPurpose
MAX_STEPS30Max steps per goal before stopping
STEP_DELAY500Milliseconds between steps
MAX_ELEMENTS40Max interactive elements per screen capture
MAX_HISTORY_STEPS10Previous steps kept in LLM context
LLM_THINKINGonExtended thinking/reasoning (on or off)
LLM_THINKING_BUDGET128Token budget for thinking
LLM_SCREENSHOT_MAX_EDGE_PX0Downscale screenshots for LLM (try 384 or 768 to reduce cost)
SHOW_TOKEN_USAGEfalsePrint token usage and cost per step
MCP Transport
VariableDefaultPurpose
MCP_TRANSPORTstdiostdio (auto-launches appium-mcp) or sse (connect to running server)
MCP_HOSTlocalhostSSE transport: hostname
MCP_PORT8080SSE transport: port

stdio (default) — AppClaw spawns npx appium-mcp@latest as a subprocess. No manual server setup.

SSE — Connect to an already-running appium-mcp server. Useful for shared environments or debugging.

Episodic Memory
env
EPISODIC_MEMORY=on    # off by default

Records successful trajectories to ~/.appclaw/trajectories.json and reuses them for similar goals in future runs.


Safety Policy

Safe without approval:

  • appclaw --help, appclaw --version
  • appclaw --flow (YAML execution — predictable, no LLM)
  • appclaw --report (read-only report server)
  • Reading .env, .appclaw/env/, flow YAML files

Ask before executing:

  • appclaw "goal" (agent mode — uses LLM credits, takes actions on device)
  • appclaw --explore (LLM credits + device crawling)
  • appclaw --record (agent mode + saves recording)
  • appclaw / appclaw --tui (interactive device session; goals typed inside it use LLM credits — --playground is an alias for --tui)

Why: agent and explorer modes consume LLM API credits and take real actions on the connected device.


Troubleshooting

Device Issues
ProblemDiagnosisFix
"No devices found"adb devices / xcrun simctl list devicesConnect device, boot emulator/simulator
Android not detectedCheck ANDROID_HOMEexport ANDROID_HOME=$HOME/Library/Android/sdk
iOS simulator WDA failureWDA cache issueDelete ~/.cache/appium-mcp/wda/ and retry
iOS real device WDASigning requiredFollow appium-xcuitest-driver real device setup guide
Wrong device selectedMultiple devices connectedUse --udid or --device to specify
MCP Connection Issues
ProblemFix
"Failed to connect to MCP"Check that npx appium-mcp@latest runs standalone
SSE connection refusedVerify MCP_HOST and MCP_PORT match running server
Tool call timeoutCheck device USB/network, restart appium-mcp
Vision Issues
ProblemFix
Stark vision failsVerify GEMINI_API_KEY or STARK_VISION_API_KEY is set and valid
appium-mcp vision failsCheck all AI_VISION_* vars are set; verify the API URL is reachable
Vision returns wrong coordinatesTry AI_VISION_COORD_TYPE=absolute for Gemini
Element not found (DOM or vision)Enable vision fallback: VISION_MODE=fallback
Flow Execution Issues
ProblemFix
"Undefined secret"Export the shell variable: export VAR_NAME=value
"Undefined variable"Add the key to .appclaw/env/<name>.yaml under variables:
launchApp failsSet appId in the YAML header
Tap misses elementUse more specific label text; enable vision fallback
Natural language step not recognizedUse structured syntax instead (e.g., tap: "Login")
LLM Issues
ProblemFix
"API key required"Set LLM_API_KEY in .env
Model not foundCheck LLM_MODEL matches provider's model ID
High costUse cheaper models (gemini-2.0-flash, gpt-4o-mini), reduce LLM_THINKING_BUDGET, set LLM_SCREENSHOT_MAX_EDGE_PX=384
Stuck in loopStuck detection kicks in after 3 repeated screens. Increase MAX_STEPS or simplify the goal

Common Workflows

Run a YAML flow on Android
sh
appclaw --flow examples/flows/settings-wifi-on.yaml
Run a flow with environment variables
sh
appclaw --flow tests/flows/youtube-phased.yaml --env dev
Quick test on iOS simulator
sh
appclaw --platform ios --device-type simulator --tui
# In the TUI: type commands, test them, /export to YAML
Generate test flows from a PRD
sh
appclaw --explore "E-commerce app with cart and checkout" --num-flows 10 --output-dir flows/
View execution reports
sh
appclaw --report
# Open http://localhost:4173 in browser
Cost-effective setup (Gemini)
env
LLM_PROVIDER=gemini
LLM_API_KEY=your-key
LLM_MODEL=gemini-2.0-flash
AGENT_MODE=vision
VISION_LOCATE_PROVIDER=stark
GEMINI_API_KEY=your-key
LLM_SCREENSHOT_MAX_EDGE_PX=512

Gemini Flash is the cheapest vision-capable model ($0.10/M input tokens). One key covers both LLM and Stark vision.

Free local setup (Ollama)
env
LLM_PROVIDER=ollama
LLM_MODEL=llama3.2
AGENT_MODE=dom

No API key needed. Requires Ollama running locally. DOM mode recommended since local models lack vision capability.


IDE Integration (VSCode Extension)

AppClaw has a VSCode extension that communicates via JSON mode:

sh
appclaw --json "Open Settings"

The --json flag enables structured JSON event output and silences the rich terminal UI. This is used by the VSCode extension bridge — users don't need to use this flag directly.


Coordination

  • For creating or editing YAML flow files, route to the generate-appclaw-flow skill.
  • For reviewing code changes to the AppClaw codebase itself, route to the review-changes skill.

© appclawhq, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in .agents/skills/use-appclaw-cli of appclawhq/AppClaw.

Open the folder on GitHubat commit 9bbc6f1

Compare with similar skills

Use Appclaw CLI 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.

Use Appclaw CLI compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Use Appclaw CLI this skillappclawhq/AppClaw116—~4.6kAutomated safety check: NotesApache-2.0
Quality Engineering Appium MCPHoangNguyen0403/agent-skills-standard570—~1.1kAutomated safety check: PassMIT
BrowserStack Live Testinghandsontable/handsontable22k—~950Automated safety check: PassCustom licence
Mobile App Debuggingsecondsky/claude-skills227—~513Automated safety check: PassMIT
Mobilerun Docs Referencedroidrun/mobilerun9.6k—~943Automated safety check: PassMIT
Appiumblokadaorg/blokada3.3k—~3.5kAutomated safety check: PassMPL-2.0

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Questions about Use Appclaw CLI

What does Use Appclaw CLI do?

Use the AppClaw CLI to run YAML flows, start the interactive TUI shell, explore apps, record/replay sessions, configure devices, and troubleshoot. Use Appclaw CLI is an agent skill from appclawhq/AppClaw. Use the AppClaw CLI to run YAML flows, start the interactive TUI shell, explore apps, record/replay sessions, configure devices, and troubleshoot.

When should I use Use Appclaw CLI?

Use Appclaw CLI fits situations like: any request involving appclaw commands; .env configuration; debugging execution failures.

How do I install Use Appclaw CLI in Claude Code?

Run `npx skills add appclawhq/AppClaw --skill use-appclaw-cli -a claude-code`. Or copy the skill folder (.agents/skills/use-appclaw-cli in appclawhq/AppClaw) into .claude/skills/use-appclaw-cli in your project. Claude Code loads it when a task matches its description.

How do I install Use Appclaw CLI in Codex?

Run `npx skills add appclawhq/AppClaw --skill use-appclaw-cli -a codex`. Or copy the skill folder (.agents/skills/use-appclaw-cli in appclawhq/AppClaw) into .agents/skills/use-appclaw-cli in your project. Codex loads it when a task matches its description.

Can I use Use Appclaw CLI 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 appclawhq/AppClaw --skill use-appclaw-cli -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/use-appclaw-cli, .gemini/skills/use-appclaw-cli, .github/skills/use-appclaw-cli and .opencode/skills/use-appclaw-cli in your project.

What does Use Appclaw CLI need to run?

Going by SKILL.md and its folder, Use Appclaw CLI needs the command-line tools its instructions call (npm, adb, xcrun, npx and git) and credentials named LLM_API_KEY, GEMINI_API_KEY, STARK_VISION_API_KEY and AI_VISION_API_KEY. Our summary lists: Node.js; A credential in LLM_API_KEY; A credential in GEMINI_API_KEY.

Does Use Appclaw CLI access the network?

SKILL.md names 3 domains. In commands or code: github.com and generativelanguage.googleapis.com; the agent is likely to contact these when it follows the instructions. As links in the text: ollama.ai. This is read from the text; nothing was executed.

Is Use Appclaw CLI safe to install?

Our automated static check of SKILL.md found notes only (mentions a .env file), nothing it rates as a warning. It is not a guarantee. Review the folder before installing.

What licence does Use Appclaw CLI use?

Use Appclaw CLI is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Use Appclaw CLI use?

About 4.6k tokens (SKILL.md is roughly 19k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Use Appclaw CLI?

Skills that share tags, products or a category with Use Appclaw CLI: Quality Engineering Appium MCP (HoangNguyen0403/agent-skills-standard, 570 stars), BrowserStack Live Testing (handsontable/handsontable, 22k stars), Mobile App Debugging (secondsky/claude-skills, 227 stars) and Mobilerun Docs Reference (droidrun/mobilerun, 9.6k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Use Appclaw CLI?

appclawhq (a GitHub organization) maintains it in appclawhq/AppClaw, which has 116 GitHub stars. The repository holds 4 skills in this directory. The repository was last updated on September 3, 2026.

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