Analyze problem text to detect patterns, difficulty, and complexity hints.

Extract variable constraints and time/memory limits.

Estimate target audience and difficulty rating for the problem.

Identify topics, tags, and prerequisites for the problem.

Suggest multiple viable candidate algorithms or structures for the problem.

Compare multiple candidate algorithms in a detailed pros/cons comparison.

Select the single absolute best algorithm to implement for a problem.

Estimate runtime safety by validating loops/nodes against constraints.

Generate an optimal solution for the problem in the requested language.

Generate language-agnostic pseudocode for the problem.

Generate code solutions in C++, Java, and Rust.

Perform a step-by-step trace execution of the code against test cases.

Verify correctness of an approach using loop invariants or mathematical proofs.

Rigorously calculate time and space complexity of code.

Generate sample test cases (input/output/explanation) for the problem.

Identify critical edge case configurations and remedies.

Generate stress testing script, random generator, and brute-force checker.

Review user code for correctness, time complexity, bugs, TLE risk, etc.

Search for logical errors, boundary flaws, or runtime bugs in the code.

Refactor solutions to reduce runtime complexity and improve performance.

Provide progressive hints for the problem.

Explain the mechanics of a specific algorithm / data structure.

Recommend next problems that build upon this problem.