Is it safe to use in multi-threaded environments?

Yes, it utilizes thread-safe file operations with locking via safe_update_json to ensure data integrity during concurrent writes.

Can I analyze the logs with external tools?

Absolutely; the logs are stored as a standard JSON array, making them fully compatible with command-line tools like jq for querying and analysis.

How does the audit log prevent file size bloat?

The skill features an automatic rotation policy that retains only the last 10,000 entries, automatically removing older entries to prevent unbounded growth.

What data is captured in each log entry?

Each entry includes a UTC timestamp, the skill name, execution status, duration in milliseconds, an array of errors, and optional custom metadata.

Audit Logging for Betty

Name: Audit Logging for Betty
Author: epieczko

byepieczko

Analytics & Monitoring

Records and manages a comprehensive audit trail of skill executions within the Betty framework for monitoring and compliance.

About

The audit.log skill provides a centralized system for tracking the execution of skills within the Betty Framework. It captures detailed telemetry including timestamps, execution status, duration, and error reports in a standardized JSON format. This skill is essential for developers who need to maintain visibility into automated workflows, debug complex skill interactions, and ensure operational compliance through a thread-safe, self-rotating logging mechanism that prevents storage overflow.

Key Features

Automatic log rotation (retains 10,000 most recent entries)
0 GitHub stars
Centralized JSON-based audit trail tracking
Native compatibility with JSON analysis tools like jq
Thread-safe concurrent writing with file locking
Detailed execution metadata and error reporting

Use Cases

Debugging failed workflow steps and identifying execution bottlenecks
Analyzing performance metrics across framework operations
Maintaining compliance records for automated AI skill executions

About

Key Features

Automatic log rotation (retains 10,000 most recent entries)
0 GitHub stars
Centralized JSON-based audit trail tracking
Native compatibility with JSON analysis tools like jq
Thread-safe concurrent writing with file locking
Detailed execution metadata and error reporting

Use Cases

Debugging failed workflow steps and identifying execution bottlenecks
Analyzing performance metrics across framework operations
Maintaining compliance records for automated AI skill executions