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MilosJova

serve7-mcp-connectors

by MilosJova

Create Task

create_task

Create a follow-up task for a human teammate when manual handling is needed after an AI-driven interaction, assigning it to the right team or person with a description and due date.

Instructions

Create a follow-up task for a human teammate — e.g. 'call customer back with a refund confirmation' — when something needs manual handling after the AI-driven part of the interaction ends.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
titleYes
dueDateNoISO-8601 date/time the task is due, if any
assigneeYesTeam or person the task should route to, e.g. 'billing-team' or an email
descriptionYes
Behavior2/5

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

There are no annotations, so the description must carry the behavioral burden, but it only describes intent, not observable behavior. It does not mention side effects such as whether the task is immediately visible, if assignees are notified, whether tasks can be updated later, or what permissions are required.

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, well-structured sentence with no filler. It front-loads the action and purpose, and the example clarifies when this tool should be used.

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?

The description gives a solid scenario but remains thin for actual invocation: half the parameters are undocumented, there is no output-schema guidance, no sibling differentiation, and no mention of side effects or lifecycle behavior. For a mutation tool with zero annotations, this is below what an agent needs to confidently use it correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is only 50%, covering dueDate and assignee, while the required 'title' and 'description' fields are undocumented. The description's example suggests possible task content but does not map the example to specific parameter values or explain how they should be composed.

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?

The description clearly names the action ('Create a follow-up task') and the resource ('a human teammate'), and grounds it with a concrete example about calling a customer back. It reads as distinct from the sibling create_support_ticket, since this is explicitly about assigning manual follow-up to a person after automation.

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?

The description gives a clear when-to-use condition: use it when something needs manual handling after the AI-driven part of the interaction ends. It does not explicitly say when not to use it or name alternative sibling tools, but the intended context is reasonably evident.

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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