> ## Documentation Index > Fetch the complete documentation index at: https://docs.agentixhub.ai/llms.txt > Use this file to discover all available pages before exploring further. # Tasks > Track, inspect and manage tasks executed as part of job workflows The **Tasks** section lets you inspect every individual task executed within a job. Tasks represent specific interactions handled by agents, including AI conversations, media display, tool invocations and more. ## Tasks List Overview The top section displays a searchable and filterable list of all tasks, with key information like: * **Task Key**: Unique ID for the task. * **Action**: Linked action (e.g., “Talk to AI Agent”, “MCP Agent”). * **Job Key**: Parent job the task belongs to. * **Created On**: Timestamp of task creation. * **Status**: Task progress (e.g., `STARTED`). Task List Each row can be expanded to reveal full task details. ## Task Details Panel Upon expanding a task, you can review: * **Input**: Parameters passed into the task (if any). * **Output**: Execution results including, as example: * Transcripts * Token usage * TTS/STT durations * Model and provider details * **Config**: System-level runtime configuration of the task (useful for debugging). * **Timeline**: Creation and start timestamps. * **Task Actions**: A real-time log of tool executions (e.g., `show_media_to_user`) with origin/destination info and timestamps. Task Details ## ✅ Common Use Cases * 🧪 **Debugging tool behavior** (see which tool was called, when and by whom). * 📊 **Reviewing AI output** (e.g., conversation transcripts and LLM statistics). * 🛠 **Understanding configuration** passed to the agent during execution. * 👀 **Auditing** real-time activity and ensuring workflow correctness. > Tasks are the atomic building blocks of the job execution system. They give full observability into what happened, when and how.