批量整理、分类和清洗即时通讯 (IM) 软件联系人与群组的结构化工作流工具
npx skills add https://github.com/cafe3310/public-agent-skills --skill im-contact-sorter
此技能提供了一套标准化的流水线,帮助用户将缺少分类功能的 IM 软件中的联系人和群组进行整理。
整体思路是,通过界面截图 - OCR 识别 - 合并和分析,最终形成结构化的数据资产,并辅助进行清理和归档。
使用此技能时,请在工作目录中遵循以下生命周期:
01-raw: 存放原始截图 (用户输入)。02-cropped: 存放裁切和压缩后的图片 (脚本生成)。03-ocr: 存放 OCR 识别后的 YAML 片段 (LLM生成)。04-merged: 存放合并后的分类文件 (脚本生成)。05-classified: 人工调整分类的工作区 (用户操作)。06-report: 存放分析报告与操作建议 (脚本生成)。首先,用户将截图,按已有的分类文件夹放入 01-raw。例如 01-raw/everything,01-raw/working-groups 等。
然后,询问用户裁切参数 (左,上,宽,高),以去除无关 UI 元素,只保留联系人列表区域。使用以下命令裁切图片:
# 用法: python crop.py <工作目录> <子目录名> <左> <上> <宽> <高>
# 示例: 裁切 'everything' 文件夹中的图片
python <path/to/skill>/scripts/crop.py . "everything" 0 200 1000 2000
你需要为每个子目录重复此步骤,直到所有截图均裁切完成,结果保存在 02-cropped/<子目录> 中。
对图片进行原地压缩,减少传输体积。你需要为每个子目录执行以下命令:
# 用法: python compress.py <工作目录> <子目录名>
python <path/to/skill>/scripts/compress.py . "everything"
使用多模态模型识别 02-cropped 中的图片。这一步的 prompt 在 scripts/ocr.md 中定义,读取并执行它。
将结果保存到 03-ocr/<子目录>/<文件名>.yaml。
将碎片化的 YAML 合并为完整文件。
# 用法: python merge.py <工作目录>
python <path/to/skill>/scripts/merge.py .
此步将在 04-merged 中生成如 everything.yaml 的汇总文件。
Agent 需要将 04-merged 的内容复制到 05-classified。提醒用户,可以根据需要调整分类结构。
# 用法: python analyze.py <工作目录>
python <path/to/skill>/scripts/analyze.py .
脚本将:
05-classified 中的 everything 文件,注入 groups 属性,识别每个项目所属的群组分类。everything 与各二级分类,识别未分类的项目。06-report/uncategorized_people.yaml (全局漏斗:未分类的人)。06-report/uncategorized_groups.yaml (全局漏斗:未分类的群)。根据 06-report 中的报告:
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Take cafe3310/im-contact-sorter from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.