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- plurigrid/asi
- 최근 소스 활동
- 2026년 2월 16일 01:58
- 감지된 SKILL.md 언어
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- 스타
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설치 방법
기본적으로 소스를 먼저 확인하는 Prompt가 선택됩니다. 직접 명령으로 전환하거나 로컬 사본을 다운로드할 수도 있습니다.
소스 파일 검토
설치 여부를 결정하기 전에 SKILL.md와 SkillsMP에 표시된 보조 파일을 읽어 보세요.
메뉴
기본적으로 소스를 먼저 확인하는 Prompt가 선택됩니다. 직접 명령으로 전환하거나 로컬 사본을 다운로드할 수도 있습니다.
설치 여부를 결정하기 전에 SKILL.md와 SkillsMP에 표시된 보조 파일을 읽어 보세요.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
직접 명령은 검토 Prompt를 거치지 않습니다. 실행하기 전에 소스를 확인하세요.
npx skills add https://github.com/plurigrid/asi --skill gh-interactome명령은 한 줄로 유지됩니다. 복사하기 전에 가로로 스크롤해 전체 내용을 확인하세요.
로컬 사본을 원하시나요? SkillsMP에서 현재 제공할 수 있는 파일을 다운로드하세요.
SKILL.md 표시 중
| name | gh-interactome |
| description | GitHub author interaction network discovery. Maps cobordisms between |
| version | 1.0.0 |
Maps the interactome (interaction network) of GitHub contributors across discovered repos. Finds cobordisms - shared boundaries where different research communities meet.
┌─────────────────────────────────────────────────────────────────────────────┐
│ INTERACTOME STRUCTURE │
├─────────────────────────────────────────────────────────────────────────────┤
│ │
│ BlockScience ◄────── olynch ──────► ToposInstitute │
│ │ │ │ │
│ ▼ ▼ ▼ │
│ cadCAD AlgebraicJulia poly │
│ │ │ │ │
│ └──── jpfairbanks ─┴── epatters ─────┘ │
│ │
│ HoTT/Coq-HoTT ◄─── abooij ───► mortberg/cubicaltt │
│ │ │ │
│ └────── mikeshulman ──────────────────┘ │
│ │
└─────────────────────────────────────────────────────────────────────────────┘
Shared contributors:
epatters (Evan Patterson) - Catlab.jl, ACSets.jl, Topos Instituteolynch (Owen Lynch) - poly, ACSets.jl, Catlab.jl, Topos Institutejpfairbanks (James Fairbanks) - Catlab.jl, ACSets.jl, U Floridakris-brown - Catlab.jl, ACSets.jl, Topos Instituteslibkind (Sophie Libkind) - Catlab.jl, Stanford/ToposBridge repos:
| Repo | Stars | Role |
|---|---|---|
| AlgebraicJulia/Catlab.jl | 681 | Applied category theory framework |
| AlgebraicJulia/ACSets.jl | 25 | Algebraic databases |
| AlgebraicJulia/AlgebraicPetri.jl | - | Compositional Petri nets |
| ToposInstitute/poly | 113 | Polynomial functors |
Shared contributors:
abooij - HoTT/Coq-HoTT, mortberg/cubicalttmikeshulman (Mike Shulman) - HoTT, real cohesionandrejbauer (Andrej Bauer) - HoTT, constructive mathDanGrayson - HoTT, cubicaltt, AgdaBridge insight: HoTT contributors often work on multiple proof assistants.
Key contributors:
toumix (1213 commits) - DisCoPy coregiodefelice (354 commits) - DisCoPyy-richie-y (173 commits) - DisCoPyoxford-quantum-group - Organizational accountBridge insight: QNLP (Quantum NLP) research connects quantum computing to linguistics via categorical semantics.
Key contributors:
zdhNarsil (94 commits) - Awesome-GFlowNets curatorbengioe (Emmanuel Bengio) - GFlowNet contributorBridge insight: GFlowNets for molecular design connects to chemistry/synthesis domains.
| Author | Repos | Affiliation |
|---|---|---|
epatters | Catlab.jl (2304), ACSets.jl (101) | Topos Institute |
olynch | poly (1), Catlab.jl (138), ACSets.jl (92) | Topos Institute |
jpfairbanks | Catlab.jl (79), ACSets.jl (19) | U Florida |
kris-brown | Catlab.jl (63) | Topos Institute |
| Author | Repos | Affiliation |
|---|---|---|
Alizter | Coq-HoTT (2191) | - |
jdchristensen | Coq-HoTT (1175) | UWO |
JasonGross | Coq-HoTT (930) | MIT |
mikeshulman | Coq-HoTT (888) | - |
andrejbauer | Coq-HoTT (396) | Ljubljana |
| Author | Repos | Affiliation |
|---|---|---|
JEJodesty | cadCAD (731), cats (107) | BlockScience |
mzargham | cadCAD (3) | BlockScience founder |
markusbkoch | cadCAD (74) | - |
danlessa | cadCAD (37) | - |
| Author | Repos | Affiliation |
|---|---|---|
toumix | discopy (1213) | Oxford |
giodefelice | discopy (354) | - |
y-richie-y | discopy (173) | - |
| Author | Connects | Via |
|---|---|---|
olynch | Topos ↔ AlgebraicJulia | poly, Catlab, ACSets |
abooij | HoTT ↔ Cubical | Coq-HoTT, cubicaltt |
dspivak | Topos ↔ Poly | poly (186 commits) |
# Authors who connect multiple communities
BRIDGE_AUTHORS = {
"olynch": ["ToposInstitute/poly", "AlgebraicJulia/Catlab.jl", "AlgebraicJulia/ACSets.jl"],
"epatters": ["AlgebraicJulia/Catlab.jl", "AlgebraicJulia/ACSets.jl", "ToposInstitute/*"],
"abooij": ["HoTT/Coq-HoTT", "mortberg/cubicaltt"],
"jpfairbanks": ["AlgebraicJulia/Catlab.jl", "AlgebraicJulia/ACSets.jl"],
"mikeshulman": ["HoTT/Coq-HoTT", "HoTT/book"],
}
Cluster 1: Applied Category Theory
- AlgebraicJulia (epatters, olynch, jpfairbanks, kris-brown)
- Topos Institute (dspivak, olynch, epatters)
- DisCoPy (toumix, giodefelice)
Cluster 2: Type Theory / Foundations
- HoTT (Alizter, jdchristensen, mikeshulman)
- Cubical (mortberg, simhu, coquand)
- Rzk (fizruk)
Cluster 3: Complex Systems / Token Engineering
- BlockScience (mzargham, JEJodesty)
- cadCAD ecosystem
Cluster 4: Haskell Categorical
- connections (cmk)
- lattices (phadej)
- haskerwaul (sellout)
#!/usr/bin/env python3
"""
GitHub Interactome: Map author interactions across repos.
"""
# /// script
# requires-python = ">=3.11"
# dependencies = ["rich", "networkx"]
# ///
import subprocess
import json
from collections import defaultdict
def get_contributors(repo: str) -> list[dict]:
"""Get contributors for a repo via gh CLI."""
cmd = f"gh api repos/{repo}/contributors --jq '.[] | {{login, contributions}}'"
result = subprocess.run(cmd, shell=True, capture_output=True, text=True)
contributors = []
for line in result.stdout.strip().split('\n'):
if line:
contributors.append(json.loads(line))
return contributors
def build_interactome(repos: list[str]) -> dict:
"""Build author-repo bipartite graph."""
author_repos = defaultdict(list)
repo_authors = defaultdict(list)
for repo in repos:
contributors = get_contributors(repo)
for c in contributors:
author = c['login']
author_repos[author].append({
'repo': repo,
'contributions': c['contributions']
})
repo_authors[repo].append(author)
{
: (author_repos),
: (repo_authors),
}
() -> []:
bridges = []
author, repos interactome[].items():
(repos) >= min_repos:
bridges.append({
: author,
: [r[] r repos],
: (r[] r repos),
})
(bridges, key= x: (x[]), reverse=)
() -> []:
cobordisms = []
repos = (interactome[].keys())
i, repo_a (repos):
repo_b repos[i+:]:
shared = (interactome[][repo_a]) & \
(interactome[][repo_b])
shared:
cobordisms.append({
: (repo_a, repo_b),
: (shared),
: (shared),
})
(cobordisms, key= x: x[], reverse=)
# Build interactome
gh-interactome-build:
@echo "🕸️ Building GitHub Interactome..."
python3 interactome.py build
# Find bridge authors
gh-interactome-bridges:
@echo "🌉 Finding bridge authors..."
python3 interactome.py bridges
# Find cobordisms
gh-interactome-cobordisms:
@echo "🔗 Finding cobordisms..."
python3 interactome.py cobordisms
# Author lookup
gh-interactome-author login:
@echo "👤 Author: {{login}}"
gh api users/{{login}} --jq '{name, company, blog, bio}'
gh api users/{{login}}/repos --jq '.[].name' | head -10
The compositional systems approach connects:
┌─────────────────────────────────────────────────────────────────────────────┐
│ COMPOSITIONAL SYSTEMS COBORDISM │
├─────────────────────────────────────────────────────────────────────────────┤
│ │
│ UC Riverside ──── John Baez ────► AlgebraicJulia ◄─── Topos Institute │
│ │ │ │ │ │
│ │ ▼ ▼ ▼ │
│ │ Stock & Flow Catlab.jl, ACSets poly │
│ │ Diagrams │ (Spivak) │
│ │ │ │ │ │
│ └────────────────┼───────────────────┼──────────────────┘ │
│ │ │ │
│ ▼ ▼ │
│ Compositional AlgebraicPetri.jl │
│ Epidemiology AlgebraicDynamics.jl │
│ │ │ │
│ └─────────┬─────────┘ │
│ │ │
│ ▼ │
│ BlockScience │
│ (cadCAD, Token Engineering) │
│ │
└─────────────────────────────────────────────────────────────────────────────┘
"Compositional Scientific Computing with Catlab and SemanticModels" (2020)
"Compositional Modeling with Stock and Flow Diagrams" (2022)
"AlgebraicRL.jl: Compositional Reinforcement Learning"
| Concept | AlgebraicJulia | BlockScience |
|---|---|---|
| Compositionality | Operad algebras | cadCAD nested configs |
| Open systems | Undirected wiring diagrams | State variables + policies |
| Semantics | Functors to dynamical systems | Simulation runs |
| Visualization | String diagrams | System dynamics diagrams |
| Author | AlgebraicJulia | BlockScience | Academic |
|---|---|---|---|
| John Baez | Advisor/papers | - | UC Riverside |
| Sophie Libkind | AlgebraicDynamics | - | Stanford/Topos |
| James Fairbanks | Catlab core | - | U Florida |
| Evan Patterson | Catlab lead | - | Topos |
| Michael Zargham | - | cadCAD lead | BlockScience |
Conceptual Bridge: Both communities use category theory for compositional modeling of complex systems - AlgebraicJulia in scientific computing, BlockScience in cryptoeconomics/token engineering.
gh-skill-explorer - Discovery skill that feeds into thisgalois-connections - Adjunctions between domainsacsets-algebraic-databases - ACSets patternsdiscopy - String diagramsTarget organizations for interactome mapping:
| Speaker | Handle | Organization | Interactome Target |
|---|---|---|---|
| pancake | trufae | radareorg | Core r2 ecosystem (75+ repos) |
| thestr4ng3r | thestr4ng3r | rizinorg | Rizin/Cutter fork community |
| oleavr | oleavr | frida | Dynamic instrumentation ecosystem |
| xvilka | XVilka | radareorg | UEFI, radeco, decompilation |
| cryptax | cryptax | rednaga | Android security tooling |
# Build interactome for discovered repos
just gh-interactome build
# Find bridge authors
just gh-interactome bridges
# Find cobordisms between communities
just gh-interactome cobordisms
# Show author profile
just gh-interactome author olynch
# Visualize network
just gh-interactome viz
# NEW: Map r2con speaker orgs
just gh-interactome orgs radareorg rizinorg frida
Compressive Vasomotion Hypothesis (CVH) — vasomotion as a fast compression sweep that collapses ambivalent neural resonances (the Bayesian-blur problem) into a definite state. Use when modeling the ~100ms taṇhā 'grab', precision-weighting as compression forcefulness, or the generative collapse step of vasocomputational active inference.
Latched Hyperprior Hypothesis (LHH) — a sustained vascular contraction engages the smooth-muscle latch-bridge, durably freezing a circuit as a committed hyperprior isolated from global updating; unlatches when its prediction resolves. Use when modeling durable commitments, trauma/PTSD as cemented priors, latch spirals, or the cross-substrate latch (mechanical/bioelectric/immune/sheaf).
Synaptic substrate of biological active inference — long-term potentiation/depression (LTP/LTD) writes priors into synaptic weights = the learning landscape (Deep CANALs). A held vascular latch annealed long enough crystallizes into a neuron prior. Use when modeling consolidation, neuron priors, the inference→learning landscape write-path, or commit-to-disk of a held prediction.
SOC 직업 분류 기준