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KaterinaProtivenskiy

Productive.io MCP Server

Create Task

productive_create_task

Create a new task in Productive.io by providing a title and task_list_id. Find task list IDs via productive_list_tasks.

Instructions

Create a new task in Productive.io. Requires a title and task_list_id (which belongs to a project). Use productive_list_tasks with a project_id to find available task_list IDs.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
titleYesTask title
due_dateNoDue date in YYYY-MM-DD format
project_idNoProject ID the task belongs to
start_dateNoStart date in YYYY-MM-DD format
assignee_idNoPerson ID to assign. Use productive_list_people to find IDs.
descriptionNoTask description (supports markdown)
task_list_idYesTask list ID (required). Use productive_list_tasks with project_id to find task list IDs.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A3.9/5.0
Behavior2/5

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

With no annotations, the description carries the full behavioral burden, yet it says nothing about required permissions, side effects on the parent list/project, whether the call is idempotent, or what the response contains. The only added context is the structural note that task_list_id belongs to a project.

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?

Two sentences, front-loaded with the action and required inputs, followed immediately by the discovery path. No filler.

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 seven-parameter mutation tool with no annotations and no output schema, the description covers required inputs and ID discovery but omits creation semantics and return behavior, which an agent must otherwise guess.

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%, so the schema already documents all seven parameters and even repeats the ID-discovery hints. The description adds one piece of meaning beyond it: that task_list_id belongs to a project, clarifying the hierarchy an agent must respect.

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 and resource ('Create a new task in Productive.io') and the required inputs, which distinguishes it clearly from siblings like productive_get_task, productive_update_task, and productive_list_tasks.

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?

Gives an explicit prerequisite (title and task_list_id) and routes the agent to productive_list_tasks with a project_id to discover valid task_list IDs. It doesn't contrast against productive_update_task or explain when creating is inappropriate, so it stops short of the top band.

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