Best use case
topos-generate is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Topos Generation Skill (PLUS +1)
Teams using topos-generate should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/topos-generate/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How topos-generate Compares
| Feature / Agent | topos-generate | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Topos Generation Skill (PLUS +1)
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Topos Generation Skill (PLUS +1)
> Sheaf-theoretic model generation via forcing
**Trit**: +1 (PLUS)
**Color**: #D82626 (Red)
**Role**: Generator/Creator
## Core Concept
A topos E generates models via:
- **Subobject classifier** Ω (truth values)
- **Internal language** (Mitchell-Bénabou)
- **Forcing semantics** (Kripke-Joyal)
```
E^op
↓ yoneda
[E^op, Set]
↓ sheafification
Sh(E, J) ← topos!
```
## Subobject Classifier Ω
In Set: Ω = {0, 1} = Bool
In Sh(X): Ω = {open subsets of X}
In Sh(C,J): Ω = sieves
```
For any mono m: A ↣ B
∃! χ_m: B → Ω such that:
A ───→ 1
↓ ↓ true
B ──→ Ω
χ_m
```
## Internal Language (Mitchell-Bénabou)
Every topos has an internal type theory:
```
Types ↔ Objects
Terms ↔ Morphisms
Predicates ↔ Subobjects
∧, ∨, → ↔ Ω operations
∀, ∃ ↔ Quantifiers via adjoints
```
### Internal Logic
```
⟦A ∧ B⟧ = ⟦A⟧ ×_Ω ⟦B⟧
⟦A → B⟧ = Ω^{⟦A⟧ → ⟦B⟧}
⟦∀x:X. φ(x)⟧ = ∏_{x:X} ⟦φ(x)⟧
```
## Kripke-Joyal Forcing
Stage-wise truth at object U:
```
U ⊩ φ ∧ ψ ⟺ U ⊩ φ and U ⊩ ψ
U ⊩ φ → ψ ⟺ ∀f:V→U. V ⊩ φ ⟹ V ⊩ ψ
U ⊩ ∀x:X.φ ⟺ ∀f:V→U, ∀a:X(V). V ⊩ φ[a/x]
U ⊩ ∃x:X.φ ⟺ ∃ cover {Uᵢ→U}, ∃aᵢ:X(Uᵢ). Uᵢ ⊩ φ[aᵢ/x]
```
## Integration with Cider/Clojure
```clojure
(ns topos.generate
(:require [acsets.core :as acs]))
;; Subobject classifier for finite topos
(defn omega [topos]
(let [sieves (all-sieves (:site topos))]
{:object sieves
:true (maximal-sieve topos)
:false (empty-sieve)}))
;; Force a proposition at stage
(defn force [stage prop env]
(case (:type prop)
:and (and (force stage (:left prop) env)
(force stage (:right prop) env))
:implies (every? (fn [morphism]
(let [stage' (compose stage morphism)]
(if (force stage' (:antecedent prop) env)
(force stage' (:consequent prop) env)
true)))
(covers stage))
:forall (every? (fn [[morphism witness]]
(force (compose stage morphism)
(:body prop)
(assoc env (:var prop) witness)))
(all-witnesses stage (:type prop)))
:exists (some (fn [[cover witnesses]]
(every? (fn [[morph wit]]
(force (compose stage morph)
(:body prop)
(assoc env (:var prop) wit)))
(zip cover witnesses)))
(all-covers-with-witnesses stage (:type prop)))))
;; Generate model satisfying formula
(defn generate-model [topos formula]
(let [stages (objects topos)]
(for [stage stages
:when (force stage formula {})]
{:stage stage
:witnesses (collect-witnesses stage formula)})))
```
## Forcing for Set Theory
Cohen forcing generates new sets:
```
P = partial functions ω → 2 (finite approximations)
G = generic filter (added by forcing)
M[G] = { interpretation of names under G }
```
## GF(3) Triads
```
sheaf-cohomology (-1) ⊗ dialectica (0) ⊗ topos-generate (+1) = 0 ✓
temporal-coalgebra (-1) ⊗ open-games (0) ⊗ topos-generate (+1) = 0 ✓
three-match (-1) ⊗ kan-extensions (0) ⊗ topos-generate (+1) = 0 ✓
```
## Commands
```bash
# Generate subobject classifier
just topos-omega site
# Force proposition at stage
just topos-force stage "∀x. φ(x)"
# Generate satisfying model
just topos-model formula
# Internal language translation
just topos-internal formula
```
## Topos Models in Practice
| Topos | Generates | Application |
|-------|-----------|-------------|
| Set | Classical sets | Standard math |
| Sh(X) | Varying sets over X | Geometry |
| Sh(G) | G-sets | Symmetry |
| Eff | Computable functions | Computability |
| Dialectica | Proof-relevant math | Type theory |
## References
- Mac Lane & Moerdijk, "Sheaves in Geometry and Logic"
- Johnstone, "Sketches of an Elephant"
- Awodey, "Category Theory" §8
- nLab: https://ncatlab.org/nlab/show/forcingRelated Skills
topos-of-music
Guerino Mazzola's mathematical music theory - Forms, Denotators, Morphisms, and Neo-Riemannian PLR operations with Gay.jl color integration
topos-catcolab
Topos Institute's CatColab for collaborative category theory - community model building, double theories, stock and flow epidemiology, and real-time collaborative diagramming via Automerge CRDT.
topos-adhesive-rewriting
Adhesive categories for incremental query updating and pattern rewriting
effective-topos
FloxHub publication `bmorphism/effective-topos` - a comprehensive development
Topos Unified Skill
**Trit**: +1 (PLUS/Generator) | **Color**: #D82626 | **Subagent**: Generator
zx-calculus
Coecke's ZX-calculus for quantum circuit reasoning via string diagrams with Z-spiders (green) and X-spiders (red)
zulip-cogen
Zulip Cogen Skill 🐸⚡
zls-integration
zls-integration skill
zig
zig skill
zig-syrup-bci
Multimodal BCI pipeline in Zig: DSI-24 EEG, fNIRS mBLL, eye tracking IVT, LSL sync, EDF read/write, GF(3) conservation
zig-programming
zig-programming skill
zeroth-bot
Zeroth Bot - 3D-printed open-source humanoid robot platform for sim-to-real and RL research. Affordable entry point for humanoid robotics.