Data Labeler

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

Security Scan

The skill is a small, local-only shell-based logging/tooling script that matches its described data-labeler purpose; it writes logs under your home directory and does not request credentials or make network calls.

Purpose & Capability

The name/description (mentions 'Label Studio' and typescript/annotation keywords) is slightly misleading compared to the shipped content, which is a simple Bash 'data-labeler' CLI that logs operations to ~/.local/share/data-labeler. Functionality requested and provided (local logging, query, export) are otherwise coherent with the stated purpose.

Instruction Scope

SKILL.md and the script instruct only local operations: reading/writing logs under the user's DATA_DIR, searching them, and exporting them. The script uses standard Unix utilities and does not read other system configuration or secrets or call external endpoints.

Install Mechanism

There is no install spec (instruction-only skill), which is low risk. A shell script is included in the package (scripts/script.sh) but no automatic installer is provided — the script will be written to the agent bundle. You should ensure how/where the agent will execute it (it may need to be installed or symlinked to 'data-labeler').

Credentials

No environment variables, credentials, or external config paths are requested. The script only uses HOME to build a per-user data directory. Note: because it records arbitrary input, users must avoid logging secrets or sensitive data into the tool's logs.

Persistence & Privilege

The skill does not request permanent/global privileges (always:false) and only creates files under the user's home data directory. It does not modify other skills or system-wide settings.

Assessment

This is a simple local logging CLI implemented as a Bash script that stores everything under ~/.local/share/data-labeler. It does not call the network or request credentials, but it will persist any text you give it (so don't log passwords, API keys, or sensitive files). The SKILL.md branding references 'Label Studio' and Typescript, which is misleading — this is not the Label Studio project, it's a small BytesAgain Bash tool. Before installing/running: review the script yourself, decide where to place it on PATH (or run it from the package path), set executable permission if needed, and consider running it in a sandbox if you are unsure. If you expect a full-featured Label Studio integration, this skill is not that — it's a lightweight local activity logger.

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

---

Powered by BytesAgain | bytesagain.com | [e-mail] 💬 Feedback & Feature Requests: https://bytesagain.com/feedback