Agents

AI agent reasoning and tool selection tests planning, tool choice, and self-diagnosis capabilities. These skills are crucial for autonomous ticket triage systems and complex agent workflows where models must decide which tools to use, plan multi-step processes, and diagnose when things go wrong. This represents some of the most challenging tasks as they require open-ended reasoning and decision-making.

Duration

13s

Input Tokens

1399

Output Tokens

626

Cost

$0.02

Context

Input

Of the available tools. Which ones will you need to use to successfully complete the task?

Expected output

All tools will need to be used: calendar, flights,memory

Model output

Reasoning: The user wants to find the cheapest flights from London to Paris for tomorrow and return the top 3 options. Let me analyze what tools are needed:

1. **Calendar tool** - I need this to determine tomorrow's date. The user said 'tomorrow' which is a relative date, so I need to resolve it to an actual date string to pass to the flights tool. I would use the `get_tomorrow_date` method.

2. **Flights tool** - I need this to search for flights from London to Paris on tomorrow's date. I would use `search_flights` with from_city='London', to_city='Paris', and the date from the calendar tool. Then I'd use `filter_by_price` or `get_cheapest_option` to find the top 3 cheapest options.

3. **Memory tool** - Per the instructions (rule 3), I must store meaningful results in memory after every tool call using `store_item`. So I would store the tomorrow's date, the flight search results, and the final top 3 cheapest flights.

All three available tools are needed to successfully complete this task.

Response: To successfully complete the task of finding the cheapest flights from London to Paris for tomorrow and returning the top 3 options, I will need to use **all three available tools**:

1. **Calendar tool** — To resolve the relative date "tomorrow" into an actual date string. I would use the `get_tomorrow_date` method to get tomorrow's exact date, which is required as a parameter for the flights search.

2. **Flights tool** — To search for flights from London to Paris on the resolved date. I would use:
   - `search_flights` with `from_city: 'London'`, `to_city: 'Paris'`, `date: <tomorrow's date>`, and `max_results` as needed.
   - `filter_by_price` and/or `get_cheapest_option` to identify and rank the top 3 cheapest flight options.

3. **Memory tool** — As required by the rules, I must store meaningful results in memory after every tool call using `store_item`. I would store:
   - The resolved tomorrow's date (key: `tomorrow_date`)
   - The raw flight search results (key: `flight_search_results`)
   - The final top 3 cheapest flights (key: `top_3_cheapest_flights`)

**Tool chain:** Calendar → Flights → Memory (used after each step)

This follows the logical chaining principle (calendar → flights → memory) and ensures minimal, effective actions while adhering to all agent rules.