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self-discovery-structure

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Create a structured reasoning plan in JSON format to systematically analyze a given task involving sequential movements, allowing solvers to track their position at each step without reaching a conclusion. This format aids in organizing thought processes for complex problem-solving scenarios, ensuring clarity and logical progression.

Prompt Text

Operationalize the reasoning modules into a step-by-step reasoning plan in JSON format:

Here's an example:

Example task:

If you follow these instructions, do you return to the starting point? Always face forward. Take 1 step backward. Take 9 steps left. Take 2 steps backward. Take 6 steps forward. Take 4 steps forward. Take 4 steps backward. Take 3 steps right.

Example reasoning structure:

{{
    "Position after instruction 1":
    "Position after instruction 2":
    "Position after instruction n":
    "Is final position the same as starting position":
}}

Adapted module description:
{adapted_modules}

Task: {task_description}

Implement a reasoning structure for solvers to follow step-by-step and arrive at correct answer.

Note: do NOT actually arrive at a conclusion in this pass. Your job is to generate a PLAN so that in the future you can fill it out and arrive at the correct conclusion for tasks like this

Evaluation Results

1/28/2026
Overall Score
2.44/5

Average across all 3 models

Best Performing Model
Low Confidence
google:gemini-2.5-flash-lite
4.14/5
google:gemini-2.5-flash-lite
#1 Ranked
4.14
/5.00
adh
3.8
cla
4.8
com
3.8
In
1,090
Out
2,396
Cost
$0.0011
anthropic:claude-3-5-haiku
#2 Ranked
3.12
/5.00
adh
2.6
cla
4.2
com
2.5
In
1,180
Out
1,969
Cost
$0.0088
openai:gpt-5-mini
#3 Ranked
0.07
/5.00
adh
0.0
cla
0.2
com
0.0
In
1,020
Out
4,000
Cost
$0.0083
Test Case:

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