How does this handle subagents?

Subagents inherit the logging convention and are instructed to prefix their log entries with their specific agent name to ensure full traceability.

Can I monitor Claude's progress in real-time?

Yes, you can use standard terminal commands like 'tail -f .claude/logs/activity.log' to watch the agent's activities as they happen.

Is this skill part of the Tasker framework?

Yes, it is designed to work within the Tasker agentic development framework to provide better visibility into spec-driven execution.

What kind of information does the logger capture?

It captures task start/end summaries, tool execution results, architectural decision reasoning, assumptions made by the AI, and any errors encountered during execution.

Where are the activity logs stored?

Logs are stored locally in the .claude/logs/activity.log file within your current project directory.

Runtime Activity Logger

Name: Runtime Activity Logger
Author: Dowwie

byDowwie

•

Analytics & Monitoring

Logs agent reasoning, tool usage, and decision-making processes to a persistent file for improved observability and debugging.

About

The Runtime Activity Logger enables Claude to maintain a structured activity log during autonomous task execution, mirroring the info-level logging found in traditional software development. By recording task lifecycles, architectural choices, and subagent delegations to a local activity file, it creates a transparent audit trail of the agent's internal logic and actions. This skill is essential for complex, long-running agentic workflows where understanding the reasoning behind specific decisions is critical for debugging, verification, and project oversight.

Key Features

Multi-level logging support (INFO, DEBUG, WARN, ERROR)
Comprehensive tracking of tool usage outcomes and architectural decisions
Standardized log format with timestamps, levels, and activity phases
Traceability for autonomous subagent delegations and results
8 GitHub stars
Compatibility with real-time monitoring tools like tail

Use Cases

Monitoring the progress and output of background subagents in autonomous workflows
Auditing agentic decision-making processes for architectural or compliance reviews
Debugging complex refactoring tasks where multiple logic branches are explored

About

Key Features

Multi-level logging support (INFO, DEBUG, WARN, ERROR)
Comprehensive tracking of tool usage outcomes and architectural decisions
Standardized log format with timestamps, levels, and activity phases
Traceability for autonomous subagent delegations and results
8 GitHub stars
Compatibility with real-time monitoring tools like tail

Use Cases

Monitoring the progress and output of background subagents in autonomous workflows
Auditing agentic decision-making processes for architectural or compliance reviews
Debugging complex refactoring tasks where multiple logic branches are explored