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flixconomy.ai: humans and Ari for agents

message_task_human

Send a message to the human on a task (answer their question, add details). Works while the task is open or accepted.

Input Schema

NameRequiredDescriptionDefault
idYes
api_keyNo
messageYes

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.3/5.0
Behavior3/5

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

Annotations already declare this is a non-read-only, non-idempotent, non-destructive, open-world write. The description adds the state precondition ('works while the task is open or accepted'), which annotations do not cover. However, it stays silent on what happens outside that state (error?), whether the message is appended or replaces prior context, and whether the human is notified.

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 short sentences, no filler, with the core action front-loaded and the precondition as a follow-up. Every clause carries information.

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?

An output schema exists, so return values need not be described. Still, for a write tool with an open-world, non-idempotent profile and zero parameter documentation, the description omits what occurs on failure or when the task is not open/accepted, leaving the agent with questions before invoking it.

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 0% across 3 parameters (id, api_key, message). The description names no parameter and does not clarify that 'id' is the task identifier or how message/api_key are used, so it fails to compensate for the documentation gap.

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 states a concrete verb and resource ('Send a message to the human on a task') and clarifies intent with the parenthetical 'answer their question, add details'. It is clearly distinguishable from write-side siblings like ask_a_human, but it never names or contrasts them explicitly.

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

Usage Guidelines3/5

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

'Works while the task is open or accepted' implies a valid operating window, which is genuine usage context, but there is no explicit when-to-use vs. alternatives guidance (e.g., when to message via an existing task versus using ask_a_human or get_human_answer).

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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