find-package

v1.0.0

Help users locate their packages on delivery shelves by matching pickup codes to shelf photos. Trigger this skill when a user mentions finding packages, pick...

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byfjh@noroot777

Install

OpenClaw Prompt Flow

Install with OpenClaw

Best for remote or guided setup. Copy the exact prompt, then paste it into OpenClaw for noroot777/find-package.

Previewing Install & Setup.
Prompt PreviewInstall & Setup
Install the skill "find-package" (noroot777/find-package) from ClawHub.
Skill page: https://clawhub.ai/noroot777/find-package
Keep the work scoped to this skill only.
After install, inspect the skill metadata and help me finish setup.
Required binaries: python3
Use only the metadata you can verify from ClawHub; do not invent missing requirements.
Ask before making any broader environment changes.

Command Line

CLI Commands

Use the direct CLI path if you want to install manually and keep every step visible.

OpenClaw CLI

Bare skill slug

openclaw skills install find-package

ClawHub CLI

Package manager switcher

npx clawhub@latest install find-package
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Purpose & Capability
Name/description (find-package) match the contents: the skill needs image-processing (vision + a local Python script to draw boxes). The only declared runtime requirement is python3, which is appropriate for the included annotate.py script. No unrelated binaries or credentials are requested.
Instruction Scope
SKILL.md instructs the agent to extract pickup codes from user-provided images, confirm the code with the user, run the local annotate.py to draw red bounding boxes, and send annotated images via the message tool. Instructions reference only images and pickup codes; they do not ask the agent to read unrelated files, environment variables, or external endpoints.
Install Mechanism
No install spec (instruction-only) and only a small included Python script. The README notes a Pillow dependency (expected for image annotation). There are no downloads from external URLs or archive extraction steps.
Credentials
Requires no environment variables or credentials. The skill references sending messages on Telegram via the platform's message tool, but it does not request any Telegram tokens or other secrets itself (that integration is expected to be provided by the host platform).
Persistence & Privilege
The skill is not always-enabled and does not request elevated or persistent privileges. It does not modify other skills or system-wide configuration. Autonomous invocation is allowed by default (platform behavior) but is not combined with any broad credential access.
Assessment
This skill appears coherent and contains only a local Python annotation script plus instructions to use the platform's vision capability and message tool. Before installing, confirm: (1) your OpenClaw environment provides the message/Telegram integration used to deliver results; (2) Pillow (pip3 install Pillow) is available if you want to run annotate.py locally; and (3) users understand they will be sending photos (privacy of images). If your environment requires explicit credentials to send Telegram messages, ensure those credentials are stored and granted by the platform rather than the skill itself.

Like a lobster shell, security has layers — review code before you run it.

Runtime requirements

📦 Clawdis
Binspython3
latestvk97cgfryw63j84e3z9yqqxgcq983zaph
85downloads
0stars
1versions
Updated 3w ago
v1.0.0
MIT-0

Find Package (找快递)

Help users find their packages on delivery station shelves. The user provides a pickup code and shelf photos, and you identify which package matches — marking it with a red bounding box and sending the annotated image back.

Workflow

Step 1: Get the pickup code (取件码)

Ask the user for their pickup code. Speak in Chinese — this is a Chinese-locale feature.

The user may respond with:

  • Plain text: e.g. "5-2-1234" or "五号架 二层 1234"
  • A screenshot: SMS notification or 菜鸟裹裹/丰巢/中通 app screenshot containing the code

Pickup code format: Typically X-Y-ZZZZ where X = shelf/section number, Y = row/layer, ZZZZ = code digits. Variations exist — some use Chinese characters, some just numbers. Extract whatever looks like a pickup reference code.

If the user sends an image, use your vision capabilities to read the pickup code from it. Look for patterns like:

  • 取件码:5-2-1234
  • 货架号:5 取件码:1234
  • 格口:5-2-1234

Confirm the extracted code with the user before proceeding: "我识别到的取件码是 5-2-1234,对吗?"

Step 2: Get shelf photos (货架照片)

Once you have the confirmed pickup code, ask the user to take photos of the package shelves. Tell them:

"请拍一下货架的照片发给我,可以一次发多张~"

The user may send:

  • A single photo of one shelf section
  • Multiple photos covering different shelf sections

Step 3: Recognize and match

For each shelf photo the user sends:

  1. Read the image with your vision capabilities — identify all visible package labels, tracking numbers, and pickup codes on the shelf
  2. Match the detected codes against the user's pickup code
  3. If a match is found:
    • Note the bounding box coordinates (in pixels) of the matching package label
    • Use the annotation script to draw a prominent red bounding box:
python3 {baseDir}/scripts/annotate.py \
  --input /path/to/shelf_photo.jpg \
  --output /tmp/find-package-result.jpg \
  --box "x1,y1,x2,y2" \
  --label "取件码: 5-2-1234"
  • Send the annotated image back to the user via the message tool with media: "file:///tmp/find-package-result.jpg"
  1. If no match is found in this photo, tell the user and ask if there are more shelves to check

Step 4: Report results

When a package is found:

  • Send the annotated photo with the red bounding box
  • Say something like: "找到了!你的快递在这里,取件码 5-2-1234"

If the user has multiple pickup codes (they mentioned several or you detected multiple in the screenshot):

  • Track which ones have been found and which are still missing
  • After each shelf photo, report: "已找到 2/3 个快递,还有 1 个没找到(取件码:7-3-5678)"

When all packages are found:

  • "全部找到了!祝取件顺利~"

When no match found after all photos:

  • "在这些照片里没有找到你的快递,要不要再拍几张其他货架的照片?"

Important Notes

  • Always communicate in Chinese — this feature is for Chinese delivery stations (驿站/快递柜)
  • Be patient — users may be unfamiliar with taking clear shelf photos. If OCR is unclear, ask them to retake with better lighting or angle
  • The pickup code format varies by delivery company. Common formats:
    • X-Y-ZZZZ (e.g., 5-2-1234)
    • Just numbers on a label
    • QR codes (if you can't read QR, tell the user to provide the text code instead)
  • When drawing bounding boxes, make them visually prominent: thick red lines, with the pickup code label above the box
  • If the shelf photo is blurry or codes are unreadable, ask for a clearer photo rather than guessing

Sending Messages

Use the message tool with channel: "telegram":

{
  "action": "send",
  "channel": "telegram",
  "message": "请发一下你的取件码~可以直接打字,也可以截图给我"
}

Send with annotated image:

{
  "action": "send",
  "channel": "telegram",
  "message": "找到了!你的快递在红框标记的位置",
  "media": "file:///tmp/find-package-result.jpg"
}

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