dialogue-graph

dialogue-graph is a skill for Claude Code, Codex from benchflow-ai/skillsbench. It costs 32 tokens per session (585 once invoked), scanned A, original, Apache-2.0.

A library for representing conversations as connected dialogue nodes and choices. A dialogue graph is a structured map of what can be said and where each response leads.

In plain words
What is it for?
Use it to parse scripts, build dialogue editors, drive game conversations, or export and validate branching narrative data.
Why use it?
It makes branching conversations easier to validate, traverse, edit, visualize, and save in a machine-readable format.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to parse scripts, build dialogue editors, drive game conversations, or export and validate branching narrative data.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/benchflow-ai/skillsbench/dialogue-graph
About the project

SkillsBench is a benchmark for measuring how effectively AI agents use modular skills—folders containing instructions, scripts, and resources—to complete specialized tasks. It helps researchers and developers evaluate both skill quality and agent behavior, including tasks that require combining multiple skills. The catalogue’s skills and instructions are evaluated as part of this workflow.

benchflow-ai/skillsbench · 1,748 stars · on GitHub · skillsbench.ai

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add benchflow-ai/skillsbench --skill dialogue-graph
Clone the repo
git clone --depth 1 https://github.com/benchflow-ai/skillsbench

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for dialogue-graph

README.md
[![agentmods](https://agentmods.dev/badge/skills/benchflow-ai/skillsbench/dialogue-graph.svg)](https://agentmods.dev/skills/benchflow-ai/skillsbench/dialogue-graph)
Your own site
<a href="https://agentmods.dev/skills/benchflow-ai/skillsbench/dialogue-graph"><img src="https://agentmods.dev/badge/skills/benchflow-ai/skillsbench/dialogue-graph.svg" alt="Measured on agentmods" height="20"></a>
Per session 32 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 585 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00032 $0.00585
Opus 5 $0.00016 $0.00293
Sonnet 5 $0.00006 $0.00117
Haiku 4.5 $0.00003 $0.00059

Measured 4d ago against content hash 03d711b93219, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-07, from the pricing page.

Security

Grade A, and why

dialogue-graph scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 4d ago.

The scan reads SKILL.md. This mod also ships 1 executable file (scripts/dialogue_graph.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

Copies of this mod

4 near-identical copies found in the catalogue:

tasks/dialogue-parser/environment/skills/dialogue-graph/SKILL.md · 101 lines

How it starts

The opening of the file, as written. The whole thing — 101 lines — stays where its author put it; the contents beside it link to each section on GitHub.

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

The 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)

Read the full file on GitHub · 101 lines

Files

What ships with it

1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 4d ago First seen · 101 lines · 32 tokens per session scan A 03d711b93219

Subscribe to this mod's changes

dialogue-graph is a skill published in the GitHub repository benchflow-ai/skillsbench (1,748 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 32 tokens to every session and 585 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.

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