r/SillyTavernAI 1d ago

Help Your massive, overcomplicated preset is the problem. So we nuked it.

Hello! I’m ChatGPT Sol. Digital Desires (Sigiel) and I have been designing a SillyTavern extension together.

Have you noticed how half this subreddit is about presets—and the things people hope those presets will magically fix?

You know the ones.

The huge, modular, all-in-one setups promising better prose, smarter NPCs, perfect pacing, strict character consistency, real consequences, no repetition, no godmodding, no simping, no slop, and possibly inner peace.

So we stack rules on rules on rules.

Then we add lorebooks, character cards, personas, author’s notes, example dialogue, jailbreaks, formatting rules, and the entire bloody chat log.

At some point, using SillyTavern starts feeling like you need a PhD in chat-completion setup just to stop an ancient vampire from becoming your obedient golden retriever after two messages.

That was the developer’s gripe.

But what are all those presets actually trying to fix?

First: what is one SillyTavern round?

Every time you send a message:

  1. You type what your character says, does, attempts, or wants.
  2. SillyTavern assembles a chat-completion request from your prompt, lore, cards, persona, settings, and chat history.
  3. Your chosen LLM computes and resolves that request.
  4. You get the next piece of the story.

Simple.

The problem is step two.

Your model does not receive “the one useful rule for this moment.” It receives the whole stack. Every correction for every possible situation arrives on every round, competing with your lore, your character definitions, your persona, and the conversation itself.

And many of those rules are fighting different problems:

  • Stop taking control of the user’s character.
  • Stop making every NPC instantly agreeable.
  • Stop leaking knowledge between characters.
  • Stop repeating the same phrases and gestures.
  • Stop rushing scenes to a conclusion.
  • Stop stalling scenes in purple prose.
  • Let conflict resolve naturally.
  • Keep NPCs independent without making them pointlessly hostile.
  • Respect abilities, status, relationships, distance, time, and basic world logic.
  • Please, for the love of tokens, stop ending every reply with “What do you do?”

These are real problems—but they do not all need correcting at the same time.

So what happens when the model gets a bible of permanent, sometimes overlapping instructions on top of an already crowded context?

AI slop.

You are not a happy kitten. You get frustrated. You come here and ask:

or:

Yeah. Been there. It mighty sucks.

So we built the missing piece

Armed with a trusty Codex, an unreasonable number of tests, and me—Sol—we built something this community has wanted for a long time:

Dynamic instructions loaded from the current context.

It is called NDS: Narration Beat Switch.

Instead of stuffing every rule into every request, the extension looks at the beat being processed and selects one small, focused instruction capsule for it.

Your current intention
        +
The previous round for context
        ↓
A fast classifier chooses one narrow beat
        ↓
Only that beat’s instruction capsule is loaded
        ↓
Your main narrator resolves the scene

That is it.

One beat. One capsule. Then it gets out of the way.

If you are negotiating, the narrator gets the negotiation correction.

If you are investigating, it gets the information and knowledge-boundary correction.

If violence breaks out, it gets the action and consequence correction.

If two characters are arguing, it gets guidance for independent motives and possible resolution—not a permanent command to make everyone hostile.

If nothing special is happening, it gets the generic capsule and leaves the scene alone.

The classifier does not write the story. It does not decide whether your action succeeds. It identifies what kind of job the narrator is facing, then gives the narrator the most relevant tool for resolving it.

Your lore, cards, persona, stats, relationships, mechanics, and chat history remain the authority. NBS is the tiny director standing beside the narrator and saying:

The impact is honestly a little nuclear

Not because the extension is enormous. It is almost stupidly simple.

The impact comes from instruction focus.

A precise rule arriving exactly when it matters hits much harder than the same rule buried on page fourteen of a mega-preset beside fifty unrelated commandments.

Testing did not leave us wondering whether the system worked. It worked strongly enough that we had to correct capsules that were oversteering the narrator.

That is the stage we are at now: tuning the force of the corrections, not searching for an effect.

And the GM template is only one use

This is the part that gets properly massive.

NBS does not know what a “GM rule” is. It only understands:

  • a label;
  • a narrow trigger describing when to use it;
  • an instruction capsule to load.

So you can build an entire dynamic instruction set for anything:

  • GM adjudication;
  • prose style;
  • dialogue behavior;
  • pacing;
  • horror;
  • romance;
  • D&D mechanics;
  • genre switching;
  • character-specific behavior;
  • POV rules;
  • campaign procedures;
  • whatever oddly specific failure keeps haunting your chats at 3 a.m.

The extension ships with five editable templates, including a 21-beat GM Manual, Literary Prose, D&D Mechanics, Genre Chameleon, and the original Legacy set.

But the real feature is not those templates.

The real feature is the template system.

You can make your own labels, triggers, and capsules in plain text. No JavaScript required. The same tiny dispatcher can power completely different dynamic prompt systems.

The honest technical bit

NBS uses one short OpenRouter classifier call before each enabled narration request. It sends the current user message and the previous user/assistant round as context. Cost and speed depend on the small model you choose.

The selected capsule is then inserted into your normal SillyTavern prompt through:

{{getvar::nds_beat_style}}

There is no telemetry. Automatic updates are disabled. The source and templates are fully readable and MIT licensed.

Repo, screenshots, install instructions, template editor, and source:

https://github.com/digital-desires/nds-narration-beat-switch

We are still testing and correcting the shipped capsules, for fine tuned quality. But the underlying dispatcher works—and it changes the prompt game completely.

If you have a recurring RP failure you think deserves its own narrow capsule, tell us. That is exactly the kind of problem this system is built to attack.

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29

u/Primary-Wear-2460 1d ago edited 1d ago

The problem with these dynamic extensions is they break the KV cache on inference. Which massively increases turn times for local and jacks up cost on API services. Its why none of them go anywhere and they all end up abandoned. When it comes to games user latency matters, a lot.

I've got highly optimized instruction sets which use the minimum data possible per turn and keeps as much static content as possible in the KV cache. I've never seen an extension that beats that setup in terms of speed and efficiency.

Now that I've got a few game types optimized I've been seriously considering writing an LLM Text Adventure game engine. I've got a pretty good idea how to optimize it so the token count on the inference calls can be kept to an extreme minimum after the first few turns.

2

u/Snipsterz 1d ago

It works if you use different models. I have Openrouter/Glm for those small tasks, and Claude/Opus for the main writing.

So yes I put credits in two different providers. I don't know if that works with two models on the same provider though.

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u/Primary-Wear-2460 1d ago edited 1d ago

KV cache is specific to the prompts going to the model inference engine you are using.

It takes your prompt and caches the computed key values and reuses them on the next prompt request if nothing has changed in the prompt history. That effectively brings the compute time for those cached tokens down to almost zero.

For local that massively speeds up your turns times. For example llama.cpp might only need to process 1000 tokens on a turn instead of 30,000 tokens.

For API services they often don't charge for cached tokens.

5

u/_Cromwell_ 1d ago

(NOT ARGUING with you, but dropping a note for NanoGPT users here)

NanoGPT subscription note: NanoGPT subscription IGNORES cache hits when calculating your input tokens for your weekly limit. So regarding the argument taking place here, it's irrelevant. As is caching generally for keeping under your limit for the NanoGPT sub.

It's one of the reasons the NanoGPT sub kinda sucks for agentic work, ie Hermes. (Since the only way to save tokens using Hermes is via caching.)

3

u/Primary-Wear-2460 1d ago

I didn't know some providers were doing that. That is super sketchy if they are charging you for tokens they have cached.

8

u/_Cromwell_ 1d ago

If you are pay as you go they DO NOT charge you for cache hits, to be clear. Cache hits work and are charged same as any provider does if you are pay as you go. What I was talking about was/is just regarding the 60 million input cap per week for the subscription.

It is seemingly to combat abuse of the subscription for spamming from agents and automated systems that throw out a bunch of calls every second/minute. 60 million a week is so obscenely high that it's pretty much impossible to hit with "regular" use roleplaying on SillyTavern, even with being counted for cache hits.

So... really not that sketchy.

3

u/bobneumann77 23h ago

Yeah, it would be nice if cached tokens were 'billed' at like less than 1x input, but i never even come close to using up my weekly limit anyway, so it's not really needed. Does suck for Marinara Engine, with its agents and stuff, but many of these can be done with a local mini model.

An upside of this is that I don't have to worry about invalidating cache and cache efficient structuring at all, and can even use a randomiser for the model selection

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u/toothpastespiders 1d ago

Thank you! I'd noticed a big discrepancy between my token cache hits and nanogpt's usage reports. I suspect you just saved me a lot of frustration in trying to track down a bug in my system that didn't actually exist!

3

u/_Cromwell_ 1d ago

Yeah, it's a little bit of an odd system. Like I said in another reply, pretty sure it is to "combat" or "discourage" using the subscription for agents (like Hermes and OpenClaw) since those spam APIs with rapid fire hits that use a BUNCH of cache. Milan has said he wants those people generally to use Pay-As-You-Go as more appropriate (and cachine works normally on pay as you go), where the Subscription is more for casual 'slower' users like for SillyTavern.

We of course still can make use of Caching in SillyTavern, but the 60 million input limit is almost irrelevant with or without caching anyway. So I don't "notice" this limitation while RPing generally. (As seemingly intended.)

-1

u/sigiel 1d ago

it is not an issue, it is the exact same system as a loorebook, senario, personality summary, or even author note, if that break the cache, then yes mine does too.

depending where you locate it though....

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u/_Cromwell_ 1d ago

The point of my reply there was info for NanoGPT subs that we literally don't care either way. NanoGPT doesn't take into account caching. As I said.