Borrowing it
Nothing to install: this file belongs to ukanwat/aaabench. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/ukanwat/aaabench/main/.claude/skills/dialogue-systems/SKILL.mdgit clone --depth 1 https://github.com/ukanwat/aaabenchWrote 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.
[](https://agentmods.dev/skills/ukanwat/aaabench/dialogue-systems)<a href="https://agentmods.dev/skills/ukanwat/aaabench/dialogue-systems"><img src="https://agentmods.dev/badge/skills/ukanwat/aaabench/dialogue-systems/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.
<a href="https://agentmods.dev/skills/ukanwat/aaabench/dialogue-systems"><img src="https://agentmods.dev/badge/skills/ukanwat/aaabench/dialogue-systems.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00075 | $0.01874 |
| Opus 5.5 | $0.00030 | $0.00750 |
| Sonnet 5.5 | $0.00015 | $0.00375 |
| Haiku 4.5 | $0.00007 | $0.00187 |
Grade A, and why
dialogue-systems 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 1mo 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.
This is a copy
91% identical to dialogue-systems — 60 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.
How it starts
The opening of the file, as written. The whole thing — 179 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Dialogue systems
Model conversations as a graph: nodes hold lines, choices branch the flow,
conditions gate options, and variables remember what the player did. The first
real decision is build vs. buy — adopt a proven authoring tool (Ink or
Yarn Spinner) or write a small data-driven runner. This skill owns both Ink
and Yarn; the visual-novel and rpg genres consume it.
When to use
- Use to design branching conversations, choice menus, or narrative state (flags, relationship values) that affect later dialogue.
- Use to decide between Ink, Yarn Spinner, and a custom JSON/resource format.
- Use to wire a dialogue script into your game loop (advance line, present choices, run commands, resolve variables).
When not to use: for engine UI (text boxes, portraits, choice buttons), use
godot-ui-control or the engine's UI skill. For persisting narrative variables
across sessions, use save-systems. For data-as-resources in Godot/Unity, see
godot-resources / unity-scriptableobjects.
Core workflow
- Choose the authoring approach.
- Ink — prose-first, writer-friendly, weave/gather flow; great for dialogue-heavy or CYOA narrative. Integrate via ink runtime / inkle plugins.
- Yarn Spinner — node-based, explicit
<<commands>>, strong for game-driven dialogue with lots of engine hooks. - Custom runner — a JSON/resource graph + a small interpreter when you need full control or minimal dependencies. Don't build a language; build a graph.
- Define the node contract. A node yields one of: a line (speaker + text), a set of choices, a command/side-effect, or an end/jump. The runner advances through nodes and hands lines/choices to the UI.
- Separate variables from flow. Keep a variable store (booleans, numbers, strings) the dialogue reads/writes; gate choices with conditions over it.
- Localize from the start. Author with line IDs, not raw strings, so the displayed text comes from a string table keyed by locale.
- Drive it from the game loop. The runner is a state machine:
currentnode → emit content → wait for input (continue or choice) → advance. - Verify by walking branches. Exercise each choice path; confirm conditions, variable writes, and that every branch reaches an end or a valid jump.
What ships with it
2 files 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.
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.
- 1mo ago First seen · 179 lines · 75 tokens per session scan A 8c39ba14fd08
dialogue-systems is a skill published in the GitHub repository ukanwat/aaabench (385 stars, last pushed 2mo ago), licensed MIT. It adds 75 tokens to every session and 1,874 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 91% identical to dialogue-systems, differing in 60 lines, and is treated as a copy.
Other skills, from other repositories
unreal-engineer
!cat skills/shared/protocols/3d-spatial-foundations.md 2>/dev/null || echo "=== 3D Foundations not loaded ===".
unreal-playtest-agent
Domain skill - run screenshot-light PIE playtest episodes with structured entity observations, bounded semantic actions, transition polling, and in-memory traces for QA and external policy or RL runners.
unreal-level
Domain skill - Unreal Engine level and world management: inspect level state, load and save maps, read or edit world settings, and measure native collision distances in Editor or PIE worlds. Not for individual actor transform edits - use unreal-actors for that.
unreal-pie
Domain skill - Unreal Engine Play-In-Editor (PIE) closed-loop verification. Provides PIE lifecycle control (enter/pause/resume/exit), controlled input injection (no OS dependency), viewport screenshot capture, output log snapshot, performance sampling, and Automation Test execution with async job polling. Use for…
unreal-actors
Domain skill - Unreal Engine actor management: list, spawn, transform, and delete level actors. Use when inspecting or editing actors in the current Unreal Editor level. Not for Content Browser asset import/export - use unreal-assets for that.
unreal-assets
Domain skill - Unreal Engine Content Browser asset management: list, import, export, inspect, and delete assets. Use for package and asset operations in the Unreal Editor. Not for actor placement or transforms - use unreal-actors for that.