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Compare cities for a new office

Rent, salaries, talent pool, tax and travel links for each city, with a weighted ranking.

  • You start it: When you start it
  • Odyssey deep research
Use in CuiarRun from your AI agent

What it does

The task

Compare these cities for an office of headcount people who work as roles: cities. For each city, find the office rent for each square meter, the median salary for each role, the number of open jobs for the roles, the corporate tax rate, and the direct flights and flight time to headquarters. Use official sources first, and give a link for each number. Put the data in a new Google Sheet, and rank the cities with a weighted score. Explain the weights in 3 lines.

  • It works in any government site, Glassdoor, Google Flights and Google Sheets, in the workspace you pick, and signs in with passwords from your Cuiar vault.
  • It runs once, when you start it.
  • It uses Odyssey, the deep-research mode of the Pro and Team plans, and keeps a citation for each fact.

What you give it

BlankWhat to giveExample
headcountThe number of people in the new office25
rolesThe main roles in the officeSoftware engineers and customer support agents
cities2 to 5 cities, separated by commasLisbon, Krakow, Tallinn
headquartersThe city of your head officeAmsterdam

What you get back

An example run with the example values above. Your run uses your own data.

Office for 25 people (software engineers, support agents), head office in Amsterdam

CityRent/m2/monthEngineer medianSupport medianDirect flights/dayScore
Lisbon24 EUR46,000 EUR18,500 EUR77.8
Krakow17 EUR38,000 EUR14,200 EUR38.1
Tallinn16 EUR44,000 EUR19,000 EUR27.2

Corporate tax: Portugal 19%, Poland 19%, Estonia 22% on paid-out profit

Ranking: 1. Krakow, 2. Lisbon, 3. Tallinn

Weights: cost 40%, talent pool 35%, travel 25%

Sheet: Office cities, 41 sources

Run it in Cuiar

  1. 01

    Open it

    Click Use in Cuiar on this page. The side panel opens with the task in the composer.

  2. 02

    Fill in 4 blanks

    Type headcount, roles, cities and headquarters. Tab moves to the next blank.

  3. 03

    Run it

    Run sends it to the agent. Follow each step in the panel, and stop it at any time.

From the terminal

cuiar exec --odyssey "Compare these cities for an office of 25 people who work as Software engineers and customer support agents: Lisbon, Krakow, Tallinn. For each city, find the office rent for each square meter, the median salary for each role, the number of open jobs for the roles, the corporate tax rate, and the direct flights and flight time to Amsterdam. Use official sources first, and give a link for each number. Put the data in a new Google Sheet, and rank the cities with a weighted score. Explain the weights in 3 lines."

Run it from your AI agent

Claude Code, Codex, Cursor and other MCP clients reach Cuiar at https://mcp.cuiar.com/mcp. Add the server one time, then ask for the task in plain words, or call run_task yourself.

1. Add Cuiar to Claude Code

claude mcp add --transport http cuiar https://mcp.cuiar.com/mcp

2. Ask your agent

Use the Cuiar tool run_task to run my "Compare cities for a new office" template with headcount = 25; roles = Software engineers and customer support agents; cities = Lisbon, Krakow, Tallinn; headquarters = Amsterdam.

Setup for other agents: AI agents.

The tool call

{
  "name": "run_task",
  "arguments": {
    "task": "Compare these cities for an office of 25 people who work as Software engineers and customer support agents: Lisbon, Krakow, Tallinn. For each city, find the office rent for each square meter, the median salary for each role, the number of open jobs for the roles, the corporate tax rate, and the direct flights and flight time to Amsterdam. Use official sources first, and give a link for each number. Put the data in a new Google Sheet, and rank the cities with a weighted score. Explain the weights in 3 lines.",
    "mode": "odyssey"
  }
}

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