Skillsbench dialogue-graph
A library for building, validating, visualizing, and serializing dialogue graphs. Use this when parsing scripts or creating branching narrative structures.
install
source · Clone the upstream repo
git clone https://github.com/benchflow-ai/skillsbench
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/benchflow-ai/skillsbench "$T" && mkdir -p ~/.claude/skills && cp -r "$T/tasks/dialogue-parser/environment/skills/dialogue_graph" ~/.claude/skills/benchflow-ai-skillsbench-dialogue-graph && rm -rf "$T"
manifest:
tasks/dialogue-parser/environment/skills/dialogue_graph/SKILL.mdsource content
Dialogue Graph Skill
This skill provides a
dialogue_graph module to easily build valid dialogue trees/graphs.
When to use
- Script Parsers: When converting text to data.
- Dialogue Editors: When building tools to edit conversation flow.
- Game Logic: When traversing a dialogue tree.
- Visualization: When generating visual diagrams of dialogue flows.
How to use
Import the module:
from dialogue_graph import Graph, Node, Edge
1. The Graph
Class
GraphThe main container.
graph = Graph()
2. Adding Nodes
Define content nodes.
# Regular line graph.add_node(Node(id="Start", speaker="Guard", text="Halt!", type="line")) # Choice hub graph.add_node(Node(id="Choices", type="choice"))
3. Adding Edges
Connect nodes (transitions).
# Simple transition graph.add_edge(Edge(source="Start", target="Choices")) # Choice transition (with text) graph.add_edge(Edge(source="Choices", target="End", text="1. Run away"))
4. Export
Serialize to JSON format for the engine.
data = graph.to_dict() # returns {"nodes": [...], "edges": [...]} json_str = graph.to_json()
5. Validation
Check for integrity.
errors = graph.validate() # Returns list of strings, e.g., ["Edge 'Start'->'Unk' points to missing node 'Unk'"]
6. Visualization
Generate a PNG/SVG graph diagram.
# Requires: pip install graphviz # Also requires Graphviz binary: https://graphviz.org/download/ graph.visualize('dialogue_graph') # Creates dialogue_graph.png graph.visualize('output', format='svg') # Creates output.svg
The visualization includes:
- Diamond shapes for choice nodes (light blue)
- Rounded boxes for dialogue nodes (colored by speaker)
- Bold blue edges for skill-check choices like
,[Lie][Attack] - Gray edges for regular choices
- Black edges for simple transitions
7. Loading from JSON
Load an existing dialogue graph.
# From file graph = Graph.from_file('dialogue.json') # From dict graph = Graph.from_dict({'nodes': [...], 'edges': [...]}) # From JSON string graph = Graph.from_json(json_string)