Skill: Algorithms

Domain: build | Depth: axiom

Capabilities

• Graph algorithms: shortest path, MST, centrality, community detection (networkx)
• Sorting, searching, dynamic programming
• Optimization: gradient descent, genetic algorithms, simulated annealing (scipy)
• Cryptographic primitives: hashing, entropy
• Tree structures: BST, heap, trie
• Complexity analysis tools
• Pathfinding: A*, Dijkstra, BFS, DFS

Libraries

Library	Purpose
networkx	Graph algorithms
scipy	Optimization algorithms
numpy	Array-based algorithm primitives

Module

agents/skills/algorithms.py

Key Functions

• shortest_path(graph, src, dst) — Dijkstra shortest path
• mst(graph) — minimum spanning tree
• centrality(graph) — betweenness + eigenvector centrality
• astar(grid, start, goal, heuristic) — A* pathfinding
• genetic_optimize(fitness_fn, population, generations) — genetic algorithm
• entropy(data) — Shannon entropy
• topological_sort(dag) — topological ordering