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by cdmx-in

get_project_tasks

Retrieve tasks from a specific Goodday project, including options for closed tasks and subfolder tasks, to manage project workflows effectively.

Instructions

Get tasks from a specific project.

Args: project_id: The ID of the project closed: Set to true to retrieve all open and closed tasks subfolders: Set to true to return tasks from project subfolders

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
project_idYes
closedNo
subfoldersNo

Implementation Reference

  • The core handler function for the MCP tool 'get_project_tasks'. It constructs the Goodday API endpoint based on project_id and optional parameters (closed, subfolders), fetches the task data using make_goodday_request, handles errors and unexpected formats, formats each task using format_task, and returns a markdown-formatted list of tasks separated by ---.
    async def get_project_tasks(project_id: str, closed: bool = False, subfolders: bool = False) -> str:
        """Get tasks from a specific project.
    
        Args:
            project_id: The ID of the project
            closed: Set to true to retrieve all open and closed tasks
            subfolders: Set to true to return tasks from project subfolders
        """
        params = []
        if closed:
            params.append("closed=true")
        if subfolders:
            params.append("subfolders=true")
        
        endpoint = f"project/{project_id}/tasks"
        if params:
            endpoint += "?" + "&".join(params)
        
        data = await make_goodday_request(endpoint)
        
        if not data:
            return "No tasks found."
        
        if isinstance(data, dict) and "error" in data:
            return f"Unable to fetch tasks: {data.get('error', 'Unknown error')}"
        
        if not isinstance(data, list):
            return f"Unexpected response format: {str(data)}"
        
        tasks = [format_task(task) for task in data]
        return "\n---\n".join(tasks)
  • Helper function used by get_project_tasks to format individual task dictionaries into a readable markdown string, safely handling nested structures like status and project.
    def format_task(task: dict) -> str:
        """Format a task into a readable string with safe checks."""
        if not isinstance(task, dict):
            return f"Invalid task data: {repr(task)}"
    
        # Defensive defaults in case nested keys are not dicts
        status = task.get('status') if isinstance(task.get('status'), dict) else {}
        project = task.get('project') if isinstance(task.get('project'), dict) else {}
    
        return f"""
    **Task ID:** {task.get('shortId', 'N/A')}
    **Title:** {task.get('name', 'N/A')}
    **Status:** {status.get('name', 'N/A')}
    **Project:** {project.get('name', 'N/A')}
    **Assigned To:** {task.get('assignedToUserId', 'N/A')}
    **Priority:** {task.get('priority', 'N/A')}
    **Start Date:** {task.get('startDate', 'N/A')}
    **End Date:** {task.get('endDate', 'N/A')}
    **Description:** {task.get('message', 'No description')}
    """.strip()
Behavior2/5

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

No annotations are provided, so the description carries full burden. It mentions retrieving tasks but doesn't disclose behavioral traits like pagination, rate limits, authentication requirements, error conditions, or what happens when project_id is invalid. The boolean parameter explanations add some context but don't cover broader operational behavior.

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

Conciseness4/5

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

The description is appropriately sized with a clear purpose statement followed by parameter explanations. The Args section is well-structured, though the initial sentence could be slightly more specific (e.g., 'Retrieve tasks...'). No wasted sentences.

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

Completeness3/5

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

For a read operation with 3 parameters and no output schema, the description covers the basics but lacks important context. It explains parameters well but doesn't describe return format, pagination, error handling, or relationship to sibling tools. Without annotations or output schema, more behavioral disclosure would be helpful.

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

Parameters4/5

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

With 0% schema description coverage, the description fully compensates by explaining all three parameters: project_id identifies the project, closed controls inclusion of completed tasks, and subfolders extends scope to nested folders. This adds meaningful semantics beyond the bare schema titles, though it doesn't specify format for project_id.

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 verb 'Get' and resource 'tasks from a specific project', making the purpose immediately understandable. It distinguishes from siblings like 'get_task' (single task) and 'get_projects' (projects list), though it doesn't explicitly contrast with 'search_goodday_tasks' or 'get_user_assigned_tasks'.

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. With siblings like 'search_goodday_tasks', 'get_user_assigned_tasks', and 'get_task', there's no indication whether this is the primary task-listing method or when project-specific filtering is preferred over other filters.

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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