Skip to main content
Glama

get_task

Read-onlyIdempotent

Fetch one KanbanFlow task by ID with full details: board, column, swimlane, labels, people, time tracking, subtasks, custom fields, and comments.

Instructions

Returns one KanbanFlow task in full: complete description, board, column, swimlane and color (with the meaning the team gave them), labels, responsible user, collaborators, time tracking, subtasks, custom fields (the raw API object) and, by default, its comments with author names and dates (read the comment text to find mentions; comment text is returned as written, not interpreted). Give a task id from list_tasks. A task is on exactly one board, so board chooses where to look and, without it, every configured board is tried until the task is found; the response says which board had it.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
boardNoBoard id or exact name the task is on (see list_boards). Default: try every configured board.
taskIdYesTask id (from list_tasks, or the last part of a kanbanflow.com/t/… URL).
includeCommentsNoFetch the task comments (default true; costs one extra API request).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive), and the description adds real operational context: comments cost one extra API request, the board fallback tries every configured board, and the response tells you which board matched. It does not describe failure/not-found behavior or rate limits, so it is not a 5.

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?

Front-loaded with the return payload, then usage, then parameter behavior; every sentence carries information. The long enumerated field list is dense but earns its place given the absence of an output schema.

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

Completeness5/5

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

With no output schema, the description enumerates the return shape thoroughly (description, board, column, swimlane, color meaning, labels, users, time tracking, subtasks, custom fields, comments with authors/dates). Nothing an agent needs to call this correctly is missing.

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?

Schema coverage is 100% (baseline 3), and the description adds genuine semantics beyond the schema: why `board` matters (a task lives on exactly one board), the all-boards fallback, and that `includeComments` costs an extra request. That justifies above-baseline credit.

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

Purpose5/5

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

States a specific verb (returns) and resource (one KanbanFlow task) and then enumerates the returned fields, so it is clearly distinguishable from list_tasks and search_tasks. The single-task retrieval scope is explicit.

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

Usage Guidelines4/5

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

Explicitly routes the agent to list_tasks for the id, and to list_boards/schema for the board name, plus explains the default all-boards search. It lacks an explicit 'when not to use this vs search_tasks' statement, so it falls short of a 5.

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