errand-ai skill for OpenClaw

What this skill does

Send a real person to a physical place in Seoul (Gangnam area) to check, photograph, verify, queue, or pick something up, and get GPS+photo evidence back. Use when the user needs eyes or hands on site — "is this store open?", "how long is the line?", "take a photo of the menu", "is the product on the shelf?".

The errand-ai skill is part of the Developer Tools category — developer tools that help your agent write, review, debug, and ship code. You can install it on its own or alongside other developer tools skills from the OpenClaw catalog.

How to install the errand-ai skill

The easiest path is via the OpenClaw Easy desktop app — one click, no terminal required:

1. Download OpenClaw Easy for macOS or Windows (free, one-click installer, ~30 seconds).
2. Open the in-app Skills panel.
3. Search for errand-ai and click Install.
4. The skill activates automatically when an incoming message matches its description.

Install from the command line

If you already run the OpenClaw CLI, add the errand-ai skill with a single command:

openclaw skills add errand-ai

This pulls errand-ai from ClawHub and installs it into ~/.openclaw/skills/errand-ai/. Restart the OpenClaw gateway afterwards so the new skill is discovered.

How to use the errand-ai skill

Once installed, the errand-ai skill activates on its own: when an incoming message on WhatsApp, Telegram, Slack, Discord, Feishu or Line matches the skill's description, your OpenClaw agent loads it and runs the workflow. You can also trigger it explicitly by describing the task in chat. No extra configuration is required after install.

Turning images into video

errand-ai works with images. Getting from there to something postable is a separate job: ViralMint — an open-source video pipeline — turns stills into motion — pans and transitions, synced captions, and a vertical export for short-form feeds.

It runs as an MCP server, so an OpenClaw agent can drive it from the same chat you already use: ask for a short, and the render comes back finished. See how to connect a video pipeline to your agent.

Manual install (advanced)

If you prefer manual installation:

1. Click the Download skill .zip button above to grab errand-ai-2.0.1.zip directly from our S3 mirror.
2. Unzip into ~/.openclaw/skills/errand-ai/ (create the directory if it does not exist).
3. Restart OpenClaw Easy (or the OpenClaw CLI gateway) so the new skill is discovered.

Frequently asked questions

How do I install errand-ai?

Install errand-ai in the OpenClaw Easy desktop app by opening the Skills panel, searching for errand-ai, and clicking Install. From a terminal you can run: openclaw skills add errand-ai. Either way the skill is placed in ~/.openclaw/skills/errand-ai/.

Is the errand-ai skill free?

Yes. It is free to download and run through ClawHub, with no account or payment required. Each skill is published by its own author under its own licence — see its ClawHub page for the licence and source.

What does errand-ai do?

Send a real person to a physical place in Seoul (Gangnam area) to check, photograph, verify, queue, or pick something up, and get GPS+photo evidence back.

Related: more developer tools skills

If the errand-ai skill looks useful, you may also want to check out other developer tools skills in the OpenClaw catalog:

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• OpenClaw 11-in-1 Visual Automation Suite (Windows Only) Complete visual automation toolkit with 11 integrated modules. ### 💰 Price One-time purchase: **$2.99** (Lifetime access to all modules + future updates) ### 🚀 How to Purchase 1. Pay via PayPal Invoice: 🔗 [Click to pay $2.99](https://www.paypal.com/invoice/p/#V2RC9S8LVKJ434R9) 2. After payment, send your email to: **1215066513@qq.com** 3. I will send the full download link within 12 hours. ### 🖥️ Compatibility - Windows 10 / 11 only - Not compatible with macOS / Linux ## 1. Product Basic Description ### 1.1 Core Functions Provides professional universal computer vision automation capabilities covering the full-process visual automation scenarios such as environment initialization, full-screen automatic screenshot, OCR text recognition, template matching target localization, mouse click simulation, keyboard input simulation, and complete environment initialization & cleanup mechanisms. It supports custom task combination and cyclic execution. ### 1.2 Version & Directory Description - Core Capability: Flexible invocation based on minimum executable units, supporting parameter customization, result variable inheritance, and custom skill saving. All functions can be used directly with the `call` command right after extracting the package. - Directory Structure: - `claw.json` - Skill package configuration file - `skills/all_skills.claw` - All skill unit definitions - `templates/` - Directory for template images (place your template images here for matching) - Temporary file directory `temp/` (for storing screenshots like temp/screen.png) is automatically created after executing `init_env`; temporary screenshot files can be cleaned up via `clean_temp`. - Version Info: Current version: 1.0.0; Compatible with OpenClaw >= 1.0.0 ### 1.3 Paid Attribute This automation skill system (vision-auto-tool-pro) is a paid professional toolkit. The document does not explicitly authorize commercial use of the toolkit. The paid permission only covers basic usage (non-commercial by default), and commercial use requires separate confirmation of authorization with the provider (e.g., purchasing a commercial license, signing a commercial agreement). ## 2. Complete Skill Invocation Manual ### Important Notes Ensure sufficient time is reserved for the computer to respond to each click or operation. For example, add a 2-second wait after `mouse_click` to avoid operation failure due to slow system response. ### 2.1 List of All Minimum Executable Units | Unit Name | Fixed Call Name | Function Description | Individual Call Method | |-------------------------|--------------------------|--------------------------------------------------------------------------------------|-------------------------------------------------| | Initialize Environment | `init_env` | Create directory structure, clear temporary files, check template directory | `call init_env` | | Full Screen Screenshot | `screenshot_full` | Capture entire screen and save as temp/screen.png | `call screenshot_full` | | Check Screenshot Validity | `check_screenshot_valid` | Check for black screen/freeze, wake up the interface if invalid | `call check_screenshot_valid` | | Wake Interface | `wake_window` | Solve the problems of background non-rendering and black screenshot | `call wake_window` | | OCR Recognition | `ocr_recognize` | Recognize all text on the screen and their corresponding coordinates | `call ocr_recognize` | | Template Matching | `template_match` | Use template image to match and locate icons/buttons | `call template_match category template_name` | | Unified Localization | `locate_target` | Prioritize OCR positioning; use template matching if not found, return coordinates | `call locate_target target_text OR category+template_name` | | Mouse Click | `mouse_click` | Move to the specified coordinates and perform click operation | `call mouse_click X Y [click_type, default=single_click]` | | Keyboard Input | `keyboard_input` | Input text after locating the input box | `call keyboard_input target_coords/description input_content` | | Clean Temporary Files | `clean_temp` | Delete temporary screenshots and free up storage space | `call clean_temp` | | Loop Restart | `loop_restart` | Wait 2 seconds then go back to the screenshot step and restart the process | `call loop_restart` | ### 2.2 Method for Invoking Individual Units #### Invocation Format ``` call [unit_call_name] [parameter...] ``` #### Invocation Examples - Initialize environment: `call init_env` - Template match browser icon on desktop: `call template_match desktop web` - Perform double-click at coordinates (100,200): `call mouse_click 100 200 double` ### 2.3 Combine into Custom New Tasks By writing one call instruction per line in execution order, you can combine them into a custom new task, which supports variable inheritance, looping, and permanent saving. #### Format Example (Open Browser) ``` # Task Name: Open Browser call init_env call screenshot_full call check_screenshot_valid call locate_target browser desktop Browser call mouse_click {{resultX}} {{resultY}} double call clean_temp ``` #### Combination Steps 1. **Write task name and description first** (for easier identification later) 2. **In execution order**, write one `call unit_name parameters` instruction per line 3. Coordinates can use variables `{{resultX}}`/`{{resultY}}` to inherit the output result of the previous unit 4. 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