Best use case
rg-flow-acset is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
RG Flow ACSet Skill
Teams using rg-flow-acset 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/rg-flow-acset/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How rg-flow-acset Compares
| Feature / Agent | rg-flow-acset | 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?
RG Flow ACSet Skill
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
# RG Flow ACSet Skill
Renormalization Group flow with ACSet categorical semantics, XY model topological defects, and Powers PCT hierarchical control.
## Seed
```
741086072858456200
```
## Triadic Palette (Powers PCT Cascade)
| Color | Hue | Hex | Role |
|-------|-----|-----|------|
| Cyan | 172° | `#23C8B3` | Ordered phase |
| Purple | 292° | `#AA22BE` | Critical/BKT |
| Gold | 52° | `#E0CE51` | Converged fixed point |
## ACSet Schema: RGFlow
```julia
@present SchRGFlow(FreeSchema) begin
# Objects
Trace::Ob
EquivalenceClass::Ob
RGStep::Ob
FixedPoint::Ob
# Morphisms
condenses_to::Hom(Trace, EquivalenceClass)
transforms_via::Hom(EquivalenceClass, RGStep)
flows_to::Hom(RGStep, FixedPoint)
# Attributes
tau::Attr(RGStep, Float64)
net_charge::Attr(RGStep, Int)
hue::Attr(EquivalenceClass, Float64)
end
# Predicates (as computed attributes)
NetChargeZero(step) = net_charge(step) == 0
Ordered(step) = tau(step) < 0.893 # Below BKT
Converged(step) = abs(tau(step) - 0.5) < 0.01
```
## XY Model Configuration (τ=0.5)
```
Phase: Ordered (below BKT critical τ_c ≈ 0.893)
Defects: 2 vortex/antivortex pairs
Net topological charge: 0 (conserved)
Phenomenal bisect: τ* ≈ 0.5 (converged)
```
## Hierarchical Control (Powers PCT)
```
Level 5 (Program): "triadic" goal
↓ sets reference for
Level 4 (Transition): hue velocities [172°, 292°, 52°]
↓ sets reference for
Level 3 (Configuration): complementary angles
↓ sets reference for
Level 2 (Sensation): target hues
↓ sets reference for
Level 1 (Intensity): lightness 0.55
```
## RG Flow Semantics
The morphism chain `Trace → EquivalenceClass → RGStep → FixedPoint` implements:
1. **condenses_to**: Traces coarse-grain to equivalence classes (irrelevant operators drop)
2. **transforms_via**: Equivalence classes evolve under RG transformation
3. **flows_to**: RG steps converge to fixed points (universality)
## GF(3) Conservation
Triadic colors sum to 0 (mod 3):
- `#23C8B3` → trit 0 (identity)
- `#AA22BE` → trit +1 (creation)
- `#E0CE51` → trit -1 (annihilation)
Net charge: 0 + 1 + (-1) = 0 ✓
## Usage
```julia
using ACSets
@acset_type RGFlowACSet(SchRGFlow)
# Create instance at BKT transition
rg = @acset RGFlowACSet begin
Trace = 4
EquivalenceClass = 2
RGStep = 1
FixedPoint = 1
condenses_to = [1, 1, 2, 2]
transforms_via = [1, 1]
flows_to = [1]
tau = [0.5]
net_charge = [0]
hue = [172.0, 292.0]
end
```
## Related Skills
- `xy-model`: XY spin dynamics and BKT transition
- `phenomenal-bisect`: Temperature search for critical τ*
- `hierarchical-control`: Powers PCT cascade
- `gay-mcp`: Deterministic color generation
## Scientific Skill Interleaving
This skill connects to the K-Dense-AI/claude-scientific-skills ecosystem:
### Annotated Data
- **anndata** [○] via bicomodule
- Hub for annotated matrices
### Bibliography References
- `dynamical-systems`: 41 citations in bib.duckdb
## Cat# Integration
This skill maps to **Cat# = Comod(P)** as a bicomodule in the equipment structure:
```
Trit: 0 (ERGODIC)
Home: Prof
Poly Op: ⊗
Kan Role: Adj
Color: #26D826
```
### GF(3) Naturality
The skill participates in triads satisfying:
```
(-1) + (0) + (+1) ≡ 0 (mod 3)
```
This ensures compositional coherence in the Cat# equipment structure.Related Skills
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