graph-algorithms
Problem-solving strategies for graph algorithms in graph number theory
Profile →npx skills add parcadei/Continuous-Claude-v3 --skill graph-algorithms --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.
# Graph Algorithms ## When to Use Use this skill when working on graph-algorithms problems in graph number theory. ## Decision Tree 1. **Traversal selection** - BFS: shortest paths (unweighted), level structure - DFS: cycle detection, topological sort, SCC 2. **Shortest path algorithms** | Algorithm | Use Case | Complexity | |-----------|----------|------------| | Dijkstra | Non-negative weights | O((V+E) log V) | | Bellman-Ford | Negative weights | O(VE) | | Floyd-Warshall | All pairs | O(V^3) | 3. **Minimum Spanning Tree** - Prim's: dense graphs, greedy from vertex - Kruskal's: sparse graphs, union-find - `z3_solve.py prove "cut_property"` 4. **Network Flow** - Max-flow = min-cut (Ford-Fulkerson) - Matching via flow network - `sympy_compute.py linsolve "flow_conservation"` 5. **Graph properties** - Spectral: eigenvalues of adjacency matrix - Connectivity: via DFS/BFS - Coloring: greedy or SAT reduction ## Tool Commands ### Sympy_Adjacency ```bash uv run python -m runtime.harness scripts/sympy_compute.py eigenvalues "adjacency_matrix" ``` ### Z3_Dijkstra ```bash uv run python -m runtime.harness scripts/z3_solve.py prove "d[v] >= d[u] + w(u,v) for all edges" ``` ### Z3_Mst_Cut ```b
- When to Use
- Decision Tree
- Tool Commands
- SympyAdjacency
- Z3Dijkstra
- Z3MstCut
- SympyFlow
- Key Techniques
- Cognitive Tools Reference
uv run python -m runtime.harness scripts/sympy_compute.py eigenvalues "adjacency_matrix" uv run python -m runtime.harness scripts/z3_solve.py prove "d[v] >= d[u] + w(u,v) for all edges" uv run python -m runtime.harness scripts/z3_solve.py prove "min_edge_crossing_cut_in_mst" uv run python -m runtime.harness scripts/sympy_compute.py linsolve "flow_conservation_equations"
What does the graph-algorithms skill do?
Problem-solving strategies for graph algorithms in graph number theory
How do I install it?
Run `npx skills add parcadei/Continuous-Claude-v3 --skill graph-algorithms --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 parcadei/Continuous-Claude-v3, a repository with 3,879 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.