Agent skill

source-coding

Problem-solving strategies for source coding in information theory

parcadei3,879★ · 1 repos on radarProfile →
claude-codecan modify filesMIT
Install
npx skills add parcadei/Continuous-Claude-v3 --skill source-coding --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 1
SKILL.md size: 3 KB
Bundled scripts: none
Allowed tools: BashRead
Path: .claude/skills/math/information-theory/source-coding/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 3,879
Language: Python
Read our review of the source →

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# Source Coding ## When to Use Use this skill when working on source-coding problems in information theory. ## Decision Tree 1. **Source Coding Theorem** - Minimum average code length >= H(X) - Achievable with optimal codes - `z3_solve.py prove "shannon_bound"` 2. **Huffman Coding** - Optimal prefix-free code for known distribution - Build tree: combine two least probable symbols - Average length: H(X) <= L < H(X) + 1 - `sympy_compute.py simplify "expected_code_length"` 3. **Kraft Inequality** - For prefix-free code: sum 2^{-l_i} <= 1 - Necessary and sufficient - `z3_solve.py prove "kraft_inequality"` 4. **Arithmetic Coding** - Approaches entropy for any distribution - Encodes entire message as interval [0,1) - Practical for adaptive/unknown distributions 5. **Rate-Distortion Theory** - Lossy compression: trade rate for distortion - R(D) = min_{p(x_hat|x): E[d(X,X_hat)]<=D} I(X;X_hat) - Minimum rate to achieve distortion D - `sympy_compute.py minimize "I(X;X_hat)" --constraint "E[d] <= D"` ## Tool Commands ### Scipy_Huffman ```bash uv run python -c "print('Huffman codes for a=0.5, b=0.25, c=0.125, d=0.125: a=0, b=10, c=110, d=111')" ``` ### Sympy_Kraft ```bash uv run python -m runt

What's inside
Steps it walks through
  1. When to Use
  2. Decision Tree
  3. Tool Commands
  4. ScipyHuffman
  5. SympyKraft
  6. Z3ShannonBound
  7. Key Techniques
  8. Cognitive Tools Reference
Commands it runs
uv run python -c "print('Huffman codes for a=0.5, b=0.25, c=0.125, d=0.125: a=0, b=10, c=110, d=111')"
uv run python -m runtime.harness scripts/sympy_compute.py simplify "2**(-l1) + 2**(-l2) + 2**(-l3) + 2**(-l4)"
uv run python -m runtime.harness scripts/z3_solve.py prove "expected_length >= entropy"
More from Continuous-Claude-v3
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About this skill
What does the source-coding skill do?

Problem-solving strategies for source coding in information theory

How do I install it?

Run `npx skills add parcadei/Continuous-Claude-v3 --skill source-coding --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From parcadei/Continuous-Claude-v3, a repository with 3,879 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

Keep going