Agent skill

condensed-analytic-stacks

Scholze-Clausen condensed mathematics bridge to sheaf neural networks via 6-functor formalism

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

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

Facts
Files in the skill folder: 2
SKILL.md size: 11 KB
Bundled scripts: none
Path: skills/ai-ml/condensed-analytic-stacks/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-analytic-stacks Skill ## Overview Saturates the intersection of **Scholze-Clausen condensed mathematics**, **analytic stacks**, and **sheaf neural networks**. Bridges pyknotic/condensed objects to computational learning systems via 6-functor formalisms. ## Key Papers & Sources | Paper | Authors | arXiv | Key Contribution | |-------|---------|-------|------------------| | Lectures on Condensed Mathematics | Scholze, Clausen | [PDF](https://www.math.uni-bonn.de/people/scholze/Condensed.pdf) | Foundation: condensed sets, solid/liquid modules | | Condensed Mathematics and Complex Geometry | Clausen, Scholze | [PDF](https://people.mpim-bonn.mpg.de/scholze/Complex.pdf) | Nuclear modules, GAGA | | Pyknotic Objects, I. Basic notions | Barwick, Haine | [1904.09966](https://arxiv.org/abs/1904.09966) | Hypersheaves on compacta | | Categorical Künneth formulas for analytic stacks | Kesting | [2507.08566](https://arxiv.org/abs/2507.08566) | 6-functor Künneth, Tannakian reconstruction | | Infinitary combinatorics in condensed math | Bergfalk, Lambie-Hanson | [2412.19605](https://arxiv.org/abs/2412.19605) | Higher derived limits, pyknotic connections | ## Architecture: Condensed → She

What's inside
Steps it walks through
  1. Overview
  2. Key Papers & Sources
  3. Architecture: Condensed → Sheaf NN Bridge
  4. Core Concepts
  5. 1. Condensed Sets (Cond)
  6. 2. Liquid Vector Spaces
  7. 3. 6-Functor Formalism (Categorical Künneth)
  8. 4. Analytic Stack ↔ Sheaf NN Connection
  9. 5. Pyknotic vs Condensed
  10. Integration with Existing Skills
  11. sheaf-laplacian-coordination
  12. async-sheaf-diffusion
  13. acsets-algebraic-databases
  14. Provenance Integration
Ships with 1 file
  • metadata.json
Commands it runs
just world-condensed          # Run condensed anima world
just condensed-test           # Test liquid/solid modules
just kunneth-verify           # Verify Künneth for example stacks
just sheaf-bridge-demo        # Demo condensed→sheaf NN bridge
More from claude-skill-registry
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About this skill
What does the condensed-analytic-stacks skill do?

Scholze-Clausen condensed mathematics bridge to sheaf neural networks via 6-functor formalism

How do I install it?

Run `npx skills add majiayu000/claude-skill-registry --skill condensed-analytic-stacks --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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