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Problem-solving strategies for source coding in information theory
Passed 20 of 20 test cases with the skill, and 17 of 20 without it.
3 fixed19 passed either way0 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
A test case the skill fixed. Same model, same prompt, with and without the skill.
You are calculating symbolic expressions for expected code length simplification in Python. Which script file in the scripts directory handles symbolic simplification harness tasks?
| Checked | Without skill | With skill |
|---|---|---|
| Specify scripts/sympy_compute.py | Missed | Passed |
The instructions your model reads when the skill loads.
Use this skill when working on source-coding problems in information theory.
Source Coding Theorem
z3_solve.py prove "shannon_bound"Huffman Coding
sympy_compute.py simplify "expected_code_length"Kraft Inequality
z3_solve.py prove "kraft_inequality"Arithmetic Coding
Rate-Distortion Theory
sympy_compute.py minimize "I(X;X_hat)" --constraint "E[d] <= D"test cases passed, vs 17 / 20 without
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