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find-package查找包

Agent Skill

find-package 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

2,715

周安装

112

GitHub Stars

公开资料未说明

下载量

887
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:find-package(查找包)
来源仓库:https://github.com/noroot777/find-package
安装命令:
openclaw skills install find-package
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install find-package

简介

通过取货码匹配货架照片以定位快递包裹位置。

  • 适用于物流仓储环境下的包裹查找辅助。find-package 属于研究检索类 Skill,可作为该场景下的辅助能力补充。
  • 需上传货架图像进行AI识别比对操作。适用宿主包括 OpenClaw,接入前应确认版本、权限和运行环境要求。
  • 安装前需确认图像整理权限与数据安全措施。
  • 建议结合来源仓库核验具体用法与维护状态。

SKILL.md

name
find-package
description
Help users locate their packages on delivery shelves by matching pickup codes to shelf photos. Trigger this skill when a user mentions finding packages, picking up deliveries, or anything related to 取快递/找包裹/取件/快递柜/驿站. This includes phrases like '帮我找快递', '我要取件', '取件码是...', '快递在哪', or similar. Even if the user just sends a pickup code (like 5-2-1234) in a delivery context, activate this skill.
metadata
allowed-tools
["message"]

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"
}

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

83.73%
按下载量换算743

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

通过

权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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