oapply-colimit
oapply: Operad algebra evaluation via colimits. Composes machines/resource sharers.
npx skills add majiayu000/claude-skill-registry --skill oapply-colimit --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# oapply-colimit Skill ## Core Pattern `oapply` computes **colimit** of component diagram over wiring pattern: ```julia using AlgebraicDynamics # Pattern + components → composite composite = oapply(wiring_diagram, [machine1, machine2, ...]) ``` ## Two Composition Modes | Mode | Type | Gluing | Example | |------|------|--------|---------| | **Undirected** | ResourceSharer | Pushout (shared state) | Lotka-Volterra | | **Directed** | Machine | Wiring (signal flow) | Control systems | ## Implementation ```julia function oapply(d::UndirectedWiringDiagram, xs::Vector{ResourceSharer}) # 1. Coproduct of state spaces S = coproduct((FinSet ∘ nstates).(xs)) # 2. Pushout identifies shared variables S′ = pushout(portmap, junctions) # 3. Induced dynamics sum at junctions return ResourceSharer(induced_interface, induced_dynamics) end ``` ## GF(3) Triads ``` schema-validation (-1) ⊗ acsets (0) ⊗ oapply-colimit (+1) = 0 ✓ interval-presheaf (-1) ⊗ algebraic-dynamics (0) ⊗ oapply-colimit (+1) = 0 ✓ ``` ## References - Libkind "An Algebra of Resource Sharers" arXiv:2007.14442 - AlgebraicJulia/AlgebraicDynamics.jl
- Core Pattern
- Two Composition Modes
- Implementation
- GF(3) Triads
- References
What does the oapply-colimit skill do?
oapply: Operad algebra evaluation via colimits. Composes machines/resource sharers.
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill oapply-colimit --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.