Agent skill
sprinter-tasks
Install this agent skill to your Project
npx add-skill https://github.com/majiayu000/claude-skill-registry/tree/main/skills/data/sprinter-tasks
SKILL.md
Sprinter Task Management Skill
Description
Manage tasks in the Sprinter kanban board using MCP tools. This skill enables AI agents to create, claim, and complete tasks programmatically.
When to Use
- Tech-Lead Planning: After creating an implementation plan, use
create_tasks_batchto create tasks - Worker Agents: Use
get_next_task,claim_task, andcomplete_taskto work through tasks - Task Visibility: Use
list_tasksto see current task board state
Available Tools
Task Creation
create_task - Create a single task
mcp__sprinter__create_task(title: "Task title", description: "Optional description")
create_tasks_batch - Create multiple tasks at once (for tech-lead planning)
mcp__sprinter__create_tasks_batch(tasks: [
{title: "Task 1", description: "Description 1"},
{title: "Task 2", description: "Description 2"}
])
Task Discovery
list_tasks - List all tasks or filter by status
mcp__sprinter__list_tasks() # All tasks
mcp__sprinter__list_tasks(status: "todo") # Only todo tasks
mcp__sprinter__list_tasks(status: "in_progress")
mcp__sprinter__list_tasks(status: "done")
get_task - Get details of a specific task
mcp__sprinter__get_task(task_id: "uuid-here")
get_next_task - Get the next available unclaimed task
mcp__sprinter__get_next_task()
Task Workflow
claim_task - Atomically claim a task for work
# Claim specific task
mcp__sprinter__claim_task(agent_id: "claude-session-123", task_id: "uuid-here")
# Claim next available task
mcp__sprinter__claim_task(agent_id: "claude-session-123")
complete_task - Mark a task as done
mcp__sprinter__complete_task(agent_id: "claude-session-123", task_id: "uuid-here")
Agent Status
get_agent_status - Check agent's current state
mcp__sprinter__get_agent_status(agent_id: "claude-session-123")
Workflows
Tech-Lead: Create Tasks After Planning
After completing a plan and exiting plan mode:
- Extract tasks from the plan
- Call
create_tasks_batchwith all tasks:
mcp__sprinter__create_tasks_batch(tasks: [
{title: "Implement user authentication", description: "Add login/logout endpoints"},
{title: "Add database migrations", description: "Create users table"},
{title: "Write unit tests", description: "Test auth handlers"}
])
Worker: Process Tasks
- Poll for work:
mcp__sprinter__get_next_task()
- Claim the task (atomic - prevents race conditions):
mcp__sprinter__claim_task(agent_id: "claude-session-123", task_id: "task-uuid")
-
Work on the task - implement the required changes
-
Complete the task:
mcp__sprinter__complete_task(agent_id: "claude-session-123", task_id: "task-uuid")
- Repeat - poll for next task
Agent ID Convention
Use a consistent agent ID format for your session:
- Format:
claude-{unique-identifier} - Examples:
claude-abc123,claude-feature-auth,claude-worker-1
The agent ID is used to:
- Track which agent claimed which task
- Prevent multiple agents from claiming the same task
- Monitor agent status (idle/working)
Task Statuses
| Status | Description |
|---|---|
todo |
Task is available for claiming |
in_progress |
Task has been claimed by an agent |
done |
Task has been completed |
Best Practices
- Always claim before working - Prevents duplicate work
- Use descriptive titles - Makes task board readable
- Complete tasks promptly - Keeps agent status accurate
- Check task list - Before creating tasks, verify they don't already exist
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