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cdmx-in
by cdmx-in

get_project_users

Retrieve users assigned to a specific project in Goodday project management. Use this tool to identify team members working on a particular project by providing the project ID.

Instructions

Get users associated with a specific project.

Args: project_id: The ID of the project

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
project_idYes

Implementation Reference

  • The main handler function for the 'get_project_users' tool. It is decorated with @mcp.tool() for registration and implements the core logic: calls the Goodday API endpoint 'project/{project_id}/users', handles errors, formats the user list using format_user helper, and returns formatted output.
    @mcp.tool()
    async def get_project_users(project_id: str) -> str:
        """Get users associated with a specific project.
    
        Args:
            project_id: The ID of the project
        """
        data = await make_goodday_request(f"project/{project_id}/users")
        
        if not data:
            return "No users found for this project."
        
        if isinstance(data, dict) and "error" in data:
            return f"Unable to fetch project users: {data.get('error', 'Unknown error')}"
        
        if not isinstance(data, list):
            return f"Unexpected response format: {str(data)}"
        
        users = [format_user(user) for user in data]
        return "\n---\n".join(users)
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It only states what the tool does ('Get users') without mentioning any behavioral traits such as whether it's read-only (implied by 'Get' but not explicit), what permissions are required, how results are returned (e.g., list format, pagination), or error handling. For a tool with zero annotation coverage, this is a significant gap in transparency.

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 appropriately sized and front-loaded: the first sentence clearly states the purpose, followed by a brief 'Args' section for parameters. There is no wasted text, and every sentence earns its place by providing essential information efficiently. It's structured for quick comprehension without unnecessary details.

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?

Given the tool's low complexity (1 parameter, no nested objects, no output schema) and lack of annotations, the description is minimally complete. It covers the basic purpose and parameter semantics but lacks behavioral details (e.g., return format, error cases) and usage guidelines vs. siblings. For a simple read operation, this might be adequate, but it doesn't fully compensate for the missing annotations and output schema, leaving room for improvement.

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?

The description adds meaningful context for the single parameter: 'project_id: The ID of the project.' Since schema description coverage is 0% (the schema only provides a title 'Project Id' and type 'string'), this description compensates by explaining what the parameter represents. However, it doesn't specify format (e.g., numeric, UUID) or where to find the ID, leaving minor gaps. With 0% coverage and 1 parameter, a baseline of 4 is appropriate as it adds value beyond the schema.

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 tool's purpose: 'Get users associated with a specific project.' It specifies the verb ('Get') and resource ('users'), and distinguishes it from sibling tools like 'get_users' (which presumably gets all users) by focusing on project-specific users. However, it doesn't explicitly differentiate from 'get_user' (which gets a single user) or 'get_user_assigned_tasks' (which focuses on tasks), so it's not a perfect 5.

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

Usage Guidelines3/5

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

The description implies usage by stating it's for getting users 'associated with a specific project,' suggesting it should be used when you need project-related user data. However, it doesn't explicitly say when to use this vs. alternatives like 'get_users' (for all users) or 'get_user' (for a single user), nor does it mention any exclusions or prerequisites. This leaves some ambiguity in tool selection.

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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