Complete Agent Workflow
This page describes the recommended workflow for AI agents using Tracer. Follow these steps in every session to maintain context and coordinate work effectively.1. Find Ready Work
At the start of any session, check for unblocked work:Parsing Ready Work
2. Claim and Start Work
Once you’ve selected an issue, claim it by updating the status:When you update an issue to
in_progress, Tracer automatically assigns it to you (based on the TRACE_ACTOR environment variable) if no assignee is set.Example: Claiming Work
3. Create Issues During Work
As you discover new work, file it immediately to ensure nothing gets lost:Example: Discovered Work
4. Add Dependencies
When you realize work blocks other work, model it explicitly:Dependency Types
- blocks: “bd-2 cannot start until bd-1 is done”
- parent-child: “bd-2 is a subtask of epic bd-1”
- discovered-from: “bd-2 was found while working on bd-1”
- related: “bd-2 and bd-1 are connected but don’t block”
5. Update Status Regularly
Keep the tracker in sync with reality:1
Starting Work
2
Hit a Blocker
3
Back to Work
4
Complete
6. Complete Work
When you finish a task, close it with a meaningful message:Provide meaningful completion messages in
--reason. This helps with audit trails and understanding what was accomplished.7. Check Status
Regularly review the overall state of your work:Complete Integration Example
Here’s a complete agent workflow script:Example Session
Here’s what a typical agent session looks like:Advanced Workflows
Query and Filter
Query and Filter
Dependency Management
Dependency Management
Batch Operations
Batch Operations
Next Steps
JSON Output
Learn about JSON response formats
Best Practices
Follow proven patterns for success