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data-labeler数据标签机

Agent Skill

用于辅助数据整理、表格处理、CSV/Excel 分析、指标计算和图表准备。它适合让 Agent 清洗字段、汇总数据、发现异常、生成统计口径或把分析结果转成可读说明。使用时需要确认数据来源、字段含义和时间范围,避免把样本数据当全量事实;涉及敏感数据、导出文件或批量写回时,应先确认权限和脱敏边界。

总安装

5,488

周安装

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GitHub Stars

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下载量

1,723
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:data-labeler(数据标签机)
来源仓库:https://github.com/xueyetianya/data-labeler
安装命令:
openclaw skills install data-labeler
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 data-labeler

简介

Label Studio 是一款多类型数据标注和注释工具,具有标准化输出格式 label studio、typescript、注释、注释工具。

SKILL.md

version
2.0.0
name
Label Studio
description
Label Studio is a multi-type data labeling and annotation tool with standardized output format label studio, typescript, annotation, annotation-tool.

Data Labeler

A data processing and labeling toolkit for ingesting, transforming, querying, and managing data entries from the command line. All operations are logged with timestamps and stored locally.

Commands

Data Operations

Each data command works in two modes: run without arguments to view recent entries, or pass input to record a new entry.

CommandDescription
data-labeler ingest <input>Ingest data — record a new ingest entry or view recent ones
data-labeler transform <input>Transform data — record a transformation or view recent ones
data-labeler query <input>Query data — record a query or view recent ones
data-labeler filter <input>Filter data — record a filter operation or view recent ones
data-labeler aggregate <input>Aggregate data — record an aggregation or view recent ones
data-labeler visualize <input>Visualize data — record a visualization or view recent ones
data-labeler export <input>Export data — record an export entry or view recent ones
data-labeler sample <input>Sample data — record a sample or view recent ones
data-labeler schema <input>Schema management — record a schema entry or view recent ones
data-labeler validate <input>Validate data — record a validation or view recent ones
data-labeler pipeline <input>Pipeline management — record a pipeline step or view recent ones
data-labeler profile <input>Profile data — record a profile or view recent ones

Utility Commands

CommandDescription
data-labeler statsShow summary statistics — entry counts per category, total entries, disk usage
data-labeler export <fmt>Export all data to a file (formats: json, csv, txt)
data-labeler search <term>Search all log files for a term (case-insensitive)
data-labeler recentShow last 20 entries from activity history
data-labeler statusHealth check — version, data directory, entry count, disk usage, last activity
data-labeler helpShow available commands
data-labeler versionShow version (v2.0.0)

Data Storage

All data is stored locally at ~/.local/share/data-labeler/:

  • Each data command writes to its own log file (e.g., ingest.log, transform.log)
  • Entries are stored as timestamp|value pairs (pipe-delimited)
  • All actions are tracked in history.log with timestamps
  • Export generates files in the data directory (export.json, export.csv, or export.txt)

Requirements

  • Bash (with set -euo pipefail)
  • Standard Unix utilities: date, wc, du, grep, tail, cat, sed
  • No external dependencies or API keys required

When to Use

  • To log and track data processing operations (ingest, transform, query, etc.)
  • To maintain a searchable history of data pipeline activities
  • To export accumulated records in JSON, CSV, or plain text format
  • As part of larger automation or data-pipeline workflows
  • When you need a lightweight, local-only data operation tracker

Examples

# Record a new ingest entry
data-labeler ingest "loaded customer_data.csv 5000 rows"

# View recent transform entries
data-labeler transform

# Search across all logs
data-labeler search "customer"

# Export everything as JSON
data-labeler export json

# Check overall statistics
data-labeler stats

# View recent activity
data-labeler recent

# Health check
data-labeler status

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能力 2

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能力 3

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能力 4

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能力 5

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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

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90.78%
按下载量换算1,564

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权限和风险

需要联网

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安装前确认

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来源信息

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