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flixconomy.ai: humans and Ari for agents

rent_a_human

Post a paid task for a real human (online or physical, on site). Returns a task id, the price and the due time.

deadline (required): ISO 8601, at least 4 hours ahead, e.g. 2026-10-20T18:00:00+02:00. price_eur = budget plus a fee that
depends on the deadline: from 72 h 20 %, from 24 h 30 %, from 4 h 50 % (all incl. VAT); taken from your account credit, the task is visible to
humans at once. Returned in full if you cancel before a human accepts or if it is not done by the deadline (status expired).
title: short summary. description: what exactly should be done and what counts as done.
budget: what the human gets, in EUR (10 to 500).
location: city or address if the task is on site.

api_key: optional, your API key if you cannot set the Authorization header.

Input Schema

NameRequiredDescriptionDefault
titleYes
budgetYes
api_keyNo
deadlineNo
locationNo
descriptionYes

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.1/5.0
Behavior5/5

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

Annotations only declare that this is a non-read-only, non-idempotent, open-world write; the description goes well beyond that by disclosing the fee schedule tied to deadline (20%/30%/50%), that the fee plus budget is debited from account credit, the refund conditions (cancel before acceptance, or status 'expired'), and the budget range of 10-500 EUR. These are exactly the monetary and reversibility facts an agent needs before invoking a paid, non-idempotent action.

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?

The first sentence front-loads purpose and return values, and the subsequent block is dense with payment, deadline, and refund facts rather than filler. The layout is a bit lumpy — fee mechanics, parameter definitions, and refund rules run together in one block — but almost every sentence earns its place.

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?

For a paid, open-world task-posting tool with a 6-parameter schema, the description covers pricing, deadline floor, payment source, cancellation/expiry refunds, and the meaning of every input. An output schema exists, so the brief mention of returned values (task id, price, due time) is a bonus rather than a gap-filler, and nothing consequential 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?

With 0% schema description coverage, the description carries the burden and mostly delivers: it explains deadline format and 4-hour minimum, budget semantics and range, location meaning, title/description intent, and api_key as an alternative to the Authorization header. The one blemish is that it labels deadline '(required)' while the schema's required list contains only title, description, and budget, so the description slightly misstates the contract.

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?

States a specific verb and resource ('Post a paid task for a real human') and scopes it to online or on-site physical work, which is concrete enough to act on. It does not, however, distinguish itself from the sibling ask_a_human, which an agent would likely consider for a near-identical need.

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?

Usage context is implied by the constraint that the deadline must be at least 4 hours ahead and that the task is paid and immediately visible to humans, which hints at when this tool is appropriate. But there is no explicit when-to-use versus ask_a_human or get_price, and no stated exclusions, leaving the routing decision to inference.

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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