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ClickUp MCP Server

by DiversioTeam

create_task_chain

Create a sequence of dependent tasks in ClickUp to manage project workflows with automatic linking of task dependencies.

Instructions

Create a chain of dependent tasks

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tasksYesList of tasks to create in sequence
list_idYesList ID for the tasks
auto_linkNoAutomatically link tasks as dependencies

Implementation Reference

  • The handler function that implements the create_task_chain tool logic. It creates multiple tasks sequentially in a specified list, optionally linking them as dependencies.
    async def create_task_chain(
        self,
        tasks: List[Dict[str, Any]],
        list_id: str,
        auto_link: bool = True,
    ) -> Dict[str, Any]:
        """Create a chain of dependent tasks."""
        created_tasks = []
    
        for i, task_data in enumerate(tasks):
            # Create task
            task_request = CreateTaskRequest(
                name=task_data["title"],
                description=task_data.get("description"),
            )
    
            # Parse time estimate if provided
            if "time_estimate" in task_data:
                task_request.time_estimate = parse_duration(task_data["time_estimate"])
    
            # Link to previous task if auto_link is enabled
            if auto_link and i > 0 and created_tasks:
                task_request.links_to = created_tasks[-1]["id"]
    
            task = await self.client.create_task(list_id, task_request)
            created_tasks.append(
                {
                    "id": task.id,
                    "name": task.name,
                    "url": format_task_url(task.id),
                }
            )
    
        return {
            "created": len(created_tasks),
            "tasks": created_tasks,
            "linked": auto_link,
        }
  • The input schema definition for the create_task_chain tool, defining parameters like tasks array, list_id, and auto_link option.
    Tool(
        name="create_task_chain",
        description="Create a chain of dependent tasks",
        inputSchema={
            "type": "object",
            "properties": {
                "tasks": {
                    "type": "array",
                    "items": {
                        "type": "object",
                        "properties": {
                            "title": {"type": "string"},
                            "description": {"type": "string"},
                            "time_estimate": {"type": "string"},
                        },
                    },
                    "description": "List of tasks to create in sequence",
                },
                "list_id": {"type": "string", "description": "List ID for the tasks"},
                "auto_link": {
                    "type": "boolean",
                    "description": "Automatically link tasks as dependencies",
                },
            },
            "required": ["tasks", "list_id"],
        },
    ),
  • Registration of the create_task_chain handler in the ClickUpTools class's _tools dictionary, mapping the tool name to its implementation method.
    self._tools: Dict[str, Callable] = {
        "create_task": self.create_task,
        "get_task": self.get_task,
        "update_task": self.update_task,
        "delete_task": self.delete_task,
        "list_tasks": self.list_tasks,
        "search_tasks": self.search_tasks,
        "get_subtasks": self.get_subtasks,
        "get_task_comments": self.get_task_comments,
        "create_task_comment": self.create_task_comment,
        "get_task_status": self.get_task_status,
        "update_task_status": self.update_task_status,
        "get_assignees": self.get_assignees,
        "assign_task": self.assign_task,
        "list_spaces": self.list_spaces,
        "list_folders": self.list_folders,
        "list_lists": self.list_lists,
        "find_list_by_name": self.find_list_by_name,
        # Bulk operations
        "bulk_update_tasks": self.bulk_update_tasks,
        "bulk_move_tasks": self.bulk_move_tasks,
        # Time tracking
        "get_time_tracked": self.get_time_tracked,
        "log_time": self.log_time,
        # Templates
        "create_task_from_template": self.create_task_from_template,
        "create_task_chain": self.create_task_chain,
        # Analytics
        "get_team_workload": self.get_team_workload,
        "get_task_analytics": self.get_task_analytics,
        # User management
        "list_users": self.list_users,
        "get_current_user": self.get_current_user,
        "find_user_by_name": self.find_user_by_name,
    }
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries full burden but offers minimal behavioral insight. It mentions creating 'dependent tasks' but doesn't explain how dependencies work, what 'auto_link' does, permissions required, whether creation is atomic, or error handling. For a mutation tool with zero annotation coverage, this is inadequate.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that directly states the tool's purpose without redundancy. It's front-loaded and wastes no words, making it easy to parse quickly. Every word earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity of creating task chains with dependencies, no annotations, and no output schema, the description is insufficient. It doesn't explain behavioral aspects like dependency management, error cases, or return values. For a tool with multiple parameters and mutation behavior, more context is needed.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so parameters are well-documented in the schema. The description adds no additional meaning beyond implying sequential creation ('in sequence' from schema) and dependency linking. It doesn't clarify parameter interactions or provide examples, meeting the baseline for high schema coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('Create') and resource ('chain of dependent tasks'), making the purpose understandable. However, it doesn't differentiate from sibling tools like 'create_task' or 'create_task_from_template', which also create tasks but with different approaches. The description is specific but lacks sibling distinction.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, when to choose it over 'create_task' for single tasks or 'bulk_update_tasks' for modifications, or any context about task dependencies. Usage is implied but not explicitly stated.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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