A real-time task logging system for AI agents that automatically detects workspaces and tracks execution progress, commands, and status.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install agent-task-logger
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install agent-task-logger using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Agent Task Logger?
The Agent Task Logger is a robust logging utility designed for AI agents, drawing inspiration from the reliable Tomcat catalina.out format. It serves as a centralized system to record and display the real-time progress of tasks performed within the Openclaw Skills ecosystem. By providing a standardized structure for logs, it allows developers and operators to monitor exactly what an agent is doing, which commands are being executed, and how long each step takes.
This skill is particularly valuable for complex automation workflows where visibility into the agent's internal state is critical. It supports multi-tasking, high-precision timestamps, and automatic workspace detection, making it a seamless addition to any AI-driven development or operations environment using Openclaw Skills.
Agent Task Logger Use Cases
- Monitoring multi-step deployment pipelines and CI/CD tasks in real-time.
- Debugging agent failures by reviewing exact shell command history and error logs.
- Auditing agent performance by comparing estimated task durations against actual execution time.
- Managing concurrent agent activities across different workspaces with automated log separation.
How Agent Task Logger Works
- The skill initializes the logging environment by automatically identifying the agent workspace through environment variables or directory paths.
- A task is initiated with a unique identifier and descriptive metadata, such as estimated completion time.
- Every command executed by the agent is captured and appended to the log file with a precise millisecond timestamp.
- Real-time status updates (Success, Failure, or Warning) are recorded to provide an immediate snapshot of the task lifecycle.
- Operators can use standard CLI tools like tail to follow logs live or grep to extract performance statistics from the archived log files.
Agent Task Logger Setup
To start using this skill within the Openclaw Skills framework, follow these initialization steps:
# Initialize the log system with automatic workspace detection
初始化日志系统
# Or manually specify a workspace path
初始化日志系统 workspace=/your/custom/path
# Monitor the logs in real-time
tail -f ~/.openclaw/workspace/logs/agent-task.log
Agent Task Logger Data Schema & Taxonomy
The system organizes data using a structured log format optimized for both human readability and programmatic parsing. Logs are stored within the designated workspace directory:
| Attribute | Description | Example |
|---|---|---|
| Timestamp | Precise execution time | 04-3 月 -2026 17:38:00.000 |
| Level | Severity level of the log | INFO, WARN, ERROR, DEBUG |
| Task Context | Unique ID for the specific agent task | [agent-task-1] |
| Payload | The actual command, status, or result | 执行命令：mvn clean package |
Files are managed in a logs/ directory with support for date-based archiving (e.g., agent-task-20260304.log).
Agent Task Logger Advanced Features
- Intelligent workspace auto-discovery prioritizing environment variables like OPENCLAW_WORKSPACE.
- High-concurrency support for simultaneous task logging without data corruption.
- Integrated log rotation and archiving to manage disk space for long-running agents.
- Built-in analytics capabilities via grep patterns to calculate total success rates and task durations.
- Support for multi-language log messages including Chinese character processing for global Openclaw Skills deployments.
SKILL.md
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