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LLM token logprobs and calibration. Per-decision confidence, ECE, Brier, reliability diagrams, low-confidence triage.
Analyze LLM token logprobs and calibration. Use for per-decision confidence, ECE, Brier scores, reliability diagrams, and low-confidence triage.
回顾最近 N 天的 Claude Code 使用记录——扫描原始会话数据,按主题分组汇总"我都做了什么",并从个人操作系统视角输出模式、风险与增删建议。当用户说 /recap、"看看我这几天做了什么"、"回顾一下我最近的会话"、"这两天我用 claude 干了啥"、"活动回顾" 时使用。
基于 SOC 职业分类
正在显示 SKILL.md
| name | oapply-colimit |
| description | oapply operad algebra evaluation via colimits with Specter-style composition patterns |
| version | 1.0.0 |
Operad algebra evaluation via colimits with bidirectional navigation
Version: 1.1.0 Trit: +1 (Generator - composes systems)
oapply computes colimit of component diagram over wiring pattern:
using AlgebraicDynamics
# Pattern + components → composite
composite = oapply(wiring_diagram, [machine1, machine2, ...])
| Mode | Type | Gluing | Example |
|---|---|---|---|
| Undirected | ResourceSharer | Pushout (shared state) | Lotka-Volterra |
| Directed | Machine | Wiring (signal flow) | Control systems |
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
Navigate wiring diagrams with bidirectional paths:
using SpecterACSet
# Navigate to all boxes
select([wd_boxes, ALL], diagram)
# Navigate to all wires from a specific box
select([wd_wires, pred(w -> source_box(w) == 1)], diagram)
# Transform: rename all boxes
transform([wd_boxes, ALL, box_name], uppercase, diagram)
| Navigator | Select | Transform |
|---|---|---|
wd_boxes | All boxes | Update boxes |
wd_wires | All wires | Update wires |
wd_ports(box_id) | Ports of box | Update ports |
wd_outer_ports | Outer interface | Update interface |
Specter's comp-navs pattern mirrors oapply:
# Specter: compose navigators (fast - just allocation)
comp_navs(nav1, nav2, nav3)
# oapply: compose machines (colimit of diagram)
oapply(wiring, [machine1, machine2, machine3])
Both use composition as colimit - Specter over paths, oapply over state spaces.
# Lotka-Volterra as composed resource sharers
rabbit = ResourceSharer{Float64}([:pop], [:pop]) do u, p, t
[p.α * u[1]] # growth
end
fox = ResourceSharer{Float64}([:pop], [:pop]) do u, p, t
[-p.δ * u[1]] # decay
end
# Compose via shared population interface
predation = oapply(predation_diagram, [rabbit, fox])
# Wiring diagram → Sexp
sexp = sexp_of_wiring_diagram(diagram)
# Navigate: find all box names
box_names = select([SEXP_CHILDREN, pred(is_box), SEXP_HEAD, ATOM_VALUE], sexp)
# Roundtrip
diagram2 = wiring_diagram_of_sexp(sexp)
schema-validation (-1) ⊗ acsets (0) ⊗ oapply-colimit (+1) = 0 ✓
interval-presheaf (-1) ⊗ algebraic-dynamics (0) ⊗ oapply-colimit (+1) = 0 ✓
bisimulation-game (-1) ⊗ coequalizers (0) ⊗ oapply-colimit (+1) = 0 ✓
coequalizers (0) - Uses pushout = coproduct + coequalizer decompositionbisimulation-game (-1) - Behavioral equivalence for skill pathstopos-adhesive-rewriting (+1) - Incremental updates via coequalizersFor time-varying systems, oapply composes observable functors:
# Koopman operator: lift nonlinear → infinite-dim linear
# oapply: compose lifted systems via colimit
composed_koopman = oapply(
dynamics_diagram,
[koopman_lift(system1), koopman_lift(system2)]
)
This skill connects to the K-Dense-AI/claude-scientific-skills ecosystem:
general: 734 citations in bib.duckdbThis skill connects to Software Design for Flexibility (Hanson & Sussman, 2021):
Concepts: eval, apply, interpreter, environment
oapply-colimit (−) + SDF.Ch5 (−) + [balancer] (−) = 0
Skill Trit: -1 (MINUS - verification)
Evaluation interprets expressions. This skill processes or generates evaluable forms.
This skill maps to Cat# = Comod(P) as a bicomodule in the equipment structure:
Trit: -1 (MINUS)
Home: Prof
Poly Op: ⊗
Kan Role: Ran_K
Color: #FF6B6B
The skill participates in triads satisfying:
(-1) + (0) + (+1) ≡ 0 (mod 3)
This ensures compositional coherence in the Cat# equipment structure.