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Data Labeler

核心功能：通过命令行执行数据摄入、转换、查询、验证等十余种操作，支持查看统计、搜索历史、导出多格式数据，所有操作带时间戳本地存储，无外部依赖。典型场景：跟踪数据处理流程、维护可搜索活动历史、嵌入自动化工作流。输入为命令行指令，输出为本地日志或JSON/CSV/TXT格式文件。

xueyetianya
xueyetianya
热度 58.70
最近更新 2026-05-11 17:33:53
分类：数据依赖：代码执行应用场景：数据处理 / 报告撰写 / 工作流 / 自动化脚本

安装技能

复制下面的话术发给你的 Agent，它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill： npx secure-skills-cli add data-labeler
Metadata
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.

Command Description
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

Command Description
data-labeler stats Show 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 recent Show last 20 entries from activity history
data-labeler status Health check — version, data directory, entry count, disk usage, last activity
data-labeler help Show available commands
data-labeler version Show 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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