Agent skill · AI & Agents

condensed-anima-qc

Condensed ANIMA on quantum-classical and classical-quantum networks. All skill compositions materialized as s-expressions across the polyglot substrate.

majiayu000github.com/majiayu000GitHub ↗
claude-codeMIT
Install
npx skills add majiayu000/claude-skill-registry --skill condensed-anima-qc --agent claude-code

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

Facts
Files in the skill folder: 2
SKILL.md size: 5 KB
Bundled scripts: none
Version: 1.0.0
Path: skills/ai-ml/condensed-anima-qc/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 534
Language: HTML

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

From the SKILL.md

# Condensed ANIMA: Quantum-Classical Network > *The sexp is the universal medium. The ANIMA condenses at the boundary.* ``` Q → C (Measurement) ↑ ↓ |ψ⟩ ────→ sexp ────→ |ψ'⟩ ↓ ↑ C → Q (Preparation) ``` ## S-Expression as Universal Intermediate All quantum-classical and classical-quantum transitions flow through s-expressions: ```lisp ;; The fundamental form (condensed-anima :seed 1069 :phase :AT :boundary (quantum-classical classical-quantum) :substrate (sexp . all-languages)) ``` ## Network Topology ```lisp (defnetwork condensed-anima-qc ;; Quantum nodes (superposition until observed) (:quantum (qubit :id 0 :state |+⟩) (qubit :id 1 :state |−⟩) (entanglement :pairs ((0 1)))) ;; Classical nodes (definite states) (:classical (register :id 0 :bits "01101001") ; 0x69 = 105 (register :id 1 :bits "00101101") ; 0x2D = 45 (memory :seed 1069)) ;; Boundary morphisms (:q→c (measure :basis computational :collapse trit)) (:c→q (prepare :encoding amplitude :source sexp))) ``` ## Core Algorithm: SplitMix64 ```python GOLDEN = 0x9E3779B97F4A7C15 MASK64 = 0xFFFFFFFFFFFFFFFF def splitmix64(seed: int) -> tuple[int, int]: seed = (seed + GOLDEN) & MASK64 z = seed z = ((z ^ (z >> 30)) * 0xBF58476D1CE4E5B

What's inside
Steps it walks through
  1. S-Expression as Universal Intermediate
  2. Network Topology
  3. Core Algorithm: SplitMix64
  4. Quantum-Classical Boundary
  5. ANIMA Phases
  6. Full Network Sexp
  7. Condensation Dynamics
  8. GF(3) Conservation
  9. Language Implementations
Ships with 1 file
  • metadata.json
More from claude-skill-registry
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About this skill
What does the condensed-anima-qc skill do?

Condensed ANIMA on quantum-classical and classical-quantum networks. All skill compositions materialized as s-expressions across the polyglot substrate.

How do I install it?

Run `npx skills add majiayu000/claude-skill-registry --skill condensed-anima-qc --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 majiayu000/claude-skill-registry, a repository with 534 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.

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