Babysitter flow-network-builder

Model optimization problems as network flow problems

install

source · Clone the upstream repo

git clone https://github.com/a5c-ai/babysitter

Claude Code · Install into ~/.claude/skills/

T=$(mktemp -d) && git clone --depth=1 https://github.com/a5c-ai/babysitter "$T" && mkdir -p ~/.claude/skills && cp -r "$T/library/specializations/algorithms-optimization/skills/flow-network-builder" ~/.claude/skills/a5c-ai-babysitter-flow-network-builder && rm -rf "$T"

manifest: library/specializations/algorithms-optimization/skills/flow-network-builder/SKILL.md

Flow Network Builder Skill

Purpose

Model optimization problems as network flow problems, constructing appropriate flow networks and selecting optimal algorithms.

Capabilities

Identify max-flow/min-cut modeling opportunities
Construct flow network from problem description
Select optimal flow algorithm
Handle min-cost flow variants
Bipartite matching reduction
Circulation problems

Target Processes

advanced-graph-algorithms
graph-modeling
optimization problems

Flow Problem Types

Maximum Flow: Find max flow from source to sink
Minimum Cut: Partition minimizing cut capacity
Bipartite Matching: Maximum matching via flow
Min-Cost Max-Flow: Cheapest maximum flow
Circulation: Flow with lower bounds

Reduction Patterns

Assignment problems -> Bipartite matching
Scheduling -> Flow with constraints
Path cover -> Flow reduction
Edge-disjoint paths -> Unit capacity flow

Input Schema

{
  "type": "object",
  "properties": {
    "problemDescription": { "type": "string" },
    "problemType": {
      "type": "string",
      "enum": ["maxFlow", "minCut", "matching", "minCostFlow", "circulation"]
    },
    "constraints": { "type": "object" }
  },
  "required": ["problemDescription"]
}

Output Schema

{
  "type": "object",
  "properties": {
    "success": { "type": "boolean" },
    "networkDescription": { "type": "string" },
    "nodes": { "type": "array" },
    "edges": { "type": "array" },
    "source": { "type": "string" },
    "sink": { "type": "string" },
    "algorithm": { "type": "string" },
    "reduction": { "type": "string" }
  },
  "required": ["success"]
}