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add_label

Add a label to a task in FluentBoards project management to organize and categorize work items by specifying board, task, and label IDs.

Instructions

Add a label to a task

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
board_idYesBoard ID
task_idYesTask ID
label_idYesLabel ID

Implementation Reference

  • The handler function for the 'add_label' tool. It destructures the arguments, makes a POST request to the API endpoint `/projects/{board_id}/labels/task` with taskId and labelId, and returns a formatted response.
    async (args) => {
      const { board_id, task_id, label_id } = args;
    
      const response = await api.post(
        `/projects/${board_id}/labels/task`,
        { taskId: task_id, labelId: label_id }
      );
      return formatResponse(response.data);
    }
  • Zod schema defining the input parameters for the 'add_label' tool: board_id, task_id, and label_id, all positive integers.
    {
      board_id: z.number().int().positive().describe("Board ID"),
      task_id: z.number().int().positive().describe("Task ID"),
      label_id: z.number().int().positive().describe("Label ID"),
    },
  • Registration of the 'add_label' tool using server.tool(), including description, input schema, and handler function within the registerLabelTools function.
      "add_label",
      "Add a label to a task",
      {
        board_id: z.number().int().positive().describe("Board ID"),
        task_id: z.number().int().positive().describe("Task ID"),
        label_id: z.number().int().positive().describe("Label ID"),
      },
      async (args) => {
        const { board_id, task_id, label_id } = args;
    
        const response = await api.post(
          `/projects/${board_id}/labels/task`,
          { taskId: task_id, labelId: label_id }
        );
        return formatResponse(response.data);
      }
    );
  • src/index.ts:25-25 (registration)
    Top-level call to registerLabelTools on the main MCP server instance, which registers the 'add_label' tool among others.
    registerLabelTools(server);
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 states the action ('Add a label') which implies a write operation, but doesn't describe any behavioral traits such as permissions required, whether the operation is idempotent, error conditions (e.g., invalid IDs), or what happens on success/failure. This leaves significant gaps for a mutation tool with zero annotation coverage.

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 with zero wasted words. It is front-loaded with the core action and resource, making it immediately scannable and appropriately sized for the tool's complexity.

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 this is a mutation tool with no annotations and no output schema, the description is incomplete. It lacks crucial context such as required permissions, error handling, return values, or side effects. While the schema covers parameters well, the overall tool behavior remains underspecified for safe and effective use by an agent.

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?

The schema description coverage is 100%, with all three parameters (board_id, task_id, label_id) clearly documented in the schema. The description adds no additional parameter semantics beyond implying these IDs are needed, so it meets the baseline of 3 where the schema does the heavy lifting without compensating for any gaps.

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 ('Add a label') and target resource ('to a task'), making the purpose immediately understandable. It distinguishes from siblings like 'create_label' (which creates new labels) and 'remove_label' (which removes them), though it doesn't explicitly contrast with alternatives like 'edit_label' for modifying existing label assignments.

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 (e.g., needing existing board, task, and label IDs), when not to use it (e.g., if a label is already attached), or direct alternatives like 'edit_label' for modifying label assignments. Usage is implied but not explicitly defined.

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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