You start by giving the agent a simple instruction: 💬 Check tasks in Jira marked "In Review". If everything is done, close them.
And then the magic starts:
1) The agent’s categorizer first analyzes the prompt to understand the intent: it's a Jira workflow task involving review and resolution. Then, it identifies the key subtasks.
2) Next, the agent’s planner breaks subtasks into actions: logging into Jira, navigating to the project, finding tickets and interpreting content, testing task, reviewing code and finally resolving task.
3) The executor agent then steps in, performing each of these actions in your browser — just like a human would, but faster.
What looks like a single sentence is actually an orchestrated sequence of decisions and actions. The agent reads it, understands it, and gets it done.
Agent actions step by step
1. Planning workflow
The agent analyzes users prompt and breaks it into subtasks, then transforms every subtask into action.
2. Crawling bookmarks
The AI agent loads your bookmark list and systematically opens each link for inspection.
3. Verifying responses
The agent checks server responses, detects broken pages, and flags errors automatically.
4. Checking content freshness
The AI agent reviews publication dates and versions to identify outdated or irrelevant content.
5. Preparing a report
The AI bookmark manager compiles a clear report with working links, broken ones, and freshness notes for easy review.
6. Reporting back
After finishing the task, agent writes back to user in chat window and confirms that the task is completed.
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