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brysontang

DeltaTask MCP Server

by brysontang

finish_task

Mark tasks as completed in a task management system by providing the task ID, enabling users to track progress and maintain organized workflows.

Instructions

Mark a task as completed.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
task_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • server.py:95-98 (handler)
    The finish_task tool handler, decorated with @mcp.tool() for registration, marks a task as completed by calling TaskService.update_task_by_id.
    @mcp.tool()
    async def finish_task(task_id: str) -> dict[str, Any]:
        """Mark a task as completed."""
        return service.update_task_by_id(task_id, {"completed": True})
Behavior2/5

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

With no annotations provided, the description carries full burden for behavioral disclosure. 'Mark as completed' implies a mutation operation, but it doesn't specify whether this is reversible, if it triggers notifications, what permissions are required, or how it affects related data (e.g., subtasks). The description is too minimal for a mutation tool.

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, clear sentence with zero wasted words. It's perfectly front-loaded and appropriately sized for a simple operation, making it easy to parse quickly.

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 that there's an output schema (which handles return values), the description's minimalism is somewhat acceptable. However, for a mutation tool with no annotations and multiple sibling alternatives, it should provide more context about behavior and usage to be truly complete. It meets minimum viability but has clear gaps.

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 doesn't mention parameters, but with only one parameter (task_id) and 0% schema description coverage, the baseline would be lower. However, the tool name and description strongly imply that 'task_id' identifies which task to complete, providing sufficient semantic context for this simple case. The description effectively compensates for the schema gap through implication.

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 ('Mark as completed') and resource ('a task'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'update_task' which might also handle task completion, so it falls short of a perfect score.

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 like 'update_task' or 'delete_task'. There's no mention of prerequisites (e.g., task must exist), constraints, or typical scenarios for completion versus other operations.

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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