Agents – anthropic/claude-opus-4.5 Task

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

15s

Input Tokens

1445

Output Tokens

685

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: Let me analyze the task and determine which tools I need to use:

1. **Task Analysis**: The user wants to find the cheapest flights from London to Paris for tomorrow, returning the top 3 options.

2. **Breaking down the requirements**:
   - Need to determine 'tomorrow's date' - requires date calculation
   - Need to search for flights from London to Paris on that date
   - Need to filter/sort by price to get the cheapest options
   - Need to return top 3 results
   - Per instructions, I must store meaningful results in memory after tool calls

3. **Available tools review**:
   - **calendar**: Has `get_tomorrow_date` method - needed to get tomorrow's date
   - **flights**: Has `search_flights`, `filter_by_price`, `get_cheapest_option` methods - needed to search and find cheapest flights
   - **memory**: Has `store_item` method - needed to store results after each tool call (per rule #3)

4. **Tool chain logic**:
   - First: Use **calendar** tool to get tomorrow's date
   - Then: Store the date in **memory**
   - Then: Use **flights** tool to search flights London → Paris for that date
   - Then: Use **flights** tool to filter/sort by price and get top 3 cheapest
   - Finally: Store final results in **memory**

All three tools are necessary for successful task completion:
- **calendar**: Essential for determining tomorrow's date
- **flights**: Essential for searching and filtering flight options
- **memory**: Required by instructions (rule #3) to store results after tool calls

Response: To successfully complete this task, I will need to use **all three available tools**:

1. **calendar** - Required to get tomorrow's date using the `get_tomorrow_date` method. The flights tool requires a specific date parameter, so I must first determine what 'tomorrow' is.

2. **flights** - The core tool for this task. I will use:
   - `search_flights` to find flights from London to Paris
   - `filter_by_price` or `get_cheapest_option` to sort and identify the cheapest options
   - The `max_results` parameter can be set to retrieve the top 3 options

3. **memory** - Required per the instructions (rule #3: "Always store meaningful results in memory using the memory tool after every tool call"). I will use `store_item` to:
   - Store tomorrow's date after the calendar call
   - Store the flight search results
   - Store the final top 3 cheapest flight options

**Logical tool chain**: calendar → memory → flights → memory → (filter/sort) → memory

This ensures I follow all the agent rules while efficiently completing the user's request.

Reasoning: Let me analyze the task and determine which tools I need to use: 1. **Task Analysis**: The user wants to find the cheapest flights from London to Paris for tomorrow, returning the top 3 options. 2. **Breaking down the requirements**: - Need to determine 'tomorrow's date' - requires date calculation - Need to search for flights from London to Paris on that date - Need to filter/sort by price to get the cheapest options - Need to return top 3 results - Per instructions, I must store meaningful results in memory after tool calls 3. **Available tools review**: - **calendar**: Has `get_tomorrow_date` method - needed to get tomorrow's date - **flights**: Has `search_flights`, `filter_by_price`, `get_cheapest_option` methods - needed to search and find cheapest flights - **memory**: Has `store_item` method - needed to store results after each tool call (per rule #3) 4. **Tool chain logic**: - First: Use **calendar** tool to get tomorrow's date - Then: Store the date in **memory** - Then: Use **flights** tool to search flights London → Paris for that date - Then: Use **flights** tool to filter/sort by price and get top 3 cheapest - Finally: Store final results in **memory** All three tools are necessary for successful task completion: - **calendar**: Essential for determining tomorrow's date - **flights**: Essential for searching and filtering flight options - **memory**: Required by instructions (rule #3) to store results after tool calls Response: To successfully complete this task, I will need to use **all three available tools**: 1. **calendar** - Required to get tomorrow's date using the `get_tomorrow_date` method. The flights tool requires a specific date parameter, so I must first determine what 'tomorrow' is. 2. **flights** - The core tool for this task. I will use: - `search_flights` to find flights from London to Paris - `filter_by_price` or `get_cheapest_option` to sort and identify the cheapest options - The `max_results` parameter can be set to retrieve the top 3 options 3. **memory** - Required per the instructions (rule #3: "Always store meaningful results in memory using the memory tool after every tool call"). I will use `store_item` to: - Store tomorrow's date after the calendar call - Store the flight search results - Store the final top 3 cheapest flight options **Logical tool chain**: calendar → memory → flights → memory → (filter/sort) → memory This ensures I follow all the agent rules while efficiently completing the user's request.