dialogue-graph

dialogue-graph is a skill for Claude Code, Codex from Raidriar7170/hermes-skilleval. It costs 32 tokens per session (585 once invoked), scanned A, a copy of dialogue-graph, MIT.

A library for representing conversations as dialogue graphs: connected lines, choices, and transitions. It can turn scripts into structured data, check that the conversation flow is valid, display it as a diagram, and export it as JSON.

In plain words
What is it for?
Use it to parse scripts, build dialogue editors, create branching narrative structures, traverse conversation logic, validate graphs, visualise flows, and export dialogue data.
Why use it?
It avoids manually managing branching conversation links and helps find broken or incomplete dialogue paths.

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, create branching narrative structures, traverse conversation logic, validate graphs, visualise flows, and export dialogue data.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/raidriar7170/hermes-skilleval/skillsbench__dialogue-graph
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 Raidriar7170/hermes-skilleval --skill skillsbench__dialogue-graph
Clone the repo
git clone --depth 1 https://github.com/Raidriar7170/hermes-skilleval

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/raidriar7170/hermes-skilleval/skillsbench__dialogue-graph/github.svg)](https://agentmods.dev/skills/raidriar7170/hermes-skilleval/skillsbench__dialogue-graph)
Your own site
<a href="https://agentmods.dev/skills/raidriar7170/hermes-skilleval/skillsbench__dialogue-graph"><img src="https://agentmods.dev/badge/skills/raidriar7170/hermes-skilleval/skillsbench__dialogue-graph/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for dialogue-graph

Your own site · 80×15
<a href="https://agentmods.dev/skills/raidriar7170/hermes-skilleval/skillsbench__dialogue-graph"><img src="https://agentmods.dev/badge/skills/raidriar7170/hermes-skilleval/skillsbench__dialogue-graph.svg" alt="Reviewed on agentmods" width="80" 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.
Origin 100% copy Near-identical to another mod 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 11d ago against content hash 03d711b93219, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, 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 11d ago.

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

This is a copy

100% identical to dialogue-graph — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

artifacts/v0.3/skillsbench-pilot/v0.3-stage2-input-package-candidate-20260701T010000Z/candidate-data/skill-sources/skillsbench__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

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. 11d 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 Raidriar7170/hermes-skilleval (123 stars, last pushed 1mo ago), licensed MIT. 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. It is 100% identical to dialogue-graph, differing in 0 lines, and is treated as a copy.

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