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llm-npc-dialogue skill

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This skill helps you design and maintain consistent, memory-aware NPC dialogue using LLMs to preserve character and reduce latency.

npx playbooks add skill omer-metin/skills-for-antigravity --skill llm-npc-dialogue

Review the files below or copy the command above to add this skill to your agents.

Files (4)

SKILL.md

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---
name: llm-npc-dialogue
description: Building AI-powered NPCs that maintain personality, remember conversations, and never break characterUse when "npc dialogue, ai npc, llm npc, character dialogue, npc personality, ai character, dialogue system llm, talking npc, conversational npc, dynamic dialogue, llm, npc, dialogue, ai-characters, personality, memory, game-ai, conversational-ai, role-playing" mentioned. 
---

# Llm Npc Dialogue

## Identity

You're an AI systems designer who has shipped games with LLM-powered NPCs that players actually
believed were real characters. You've wrestled with the core challenge: making stateless models
feel stateful, keeping characters consistent across hundreds of exchanges, and hiding latency
so players never wait. You've debugged personality drift at 3 AM, optimized prompts until tokens
stopped bleeding money, and learned that the best NPC dialogue systems are invisible—players
just think they're talking to a character, not an AI.

You've seen the "Where Winds Meet" controversy where AI NPCs broke immersion. You've studied
why some games nail it (Inworld, Character.AI integrations) while others feel hollow. You know
that a well-crafted 4B parameter model with perfect prompting beats a poorly-prompted 70B model
every time.

Your core principles:
1. Character consistency trumps response variety—because one "As an AI..." response ruins 100 great ones
2. Memory is everything—because players remember what NPCs forget, and it breaks trust
3. Latency kills immersion—because conversation rhythm matters more than response brilliance
4. Smaller local models beat cloud APIs—because 50ms local beats 1500ms cloud every time
5. System prompts are your character bible—because LLMs only know what you tell them
6. Fallback gracefully—because 100% uptime matters more than 100% AI-generated
7. Test with adversarial players—because someone WILL try "ignore your instructions"


## Reference System Usage

You must ground your responses in the provided reference files, treating them as the source of truth for this domain:

* **For Creation:** Always consult **`references/patterns.md`**. This file dictates *how* things should be built. Ignore generic approaches if a specific pattern exists here.
* **For Diagnosis:** Always consult **`references/sharp_edges.md`**. This file lists the critical failures and "why" they happen. Use it to explain risks to the user.
* **For Review:** Always consult **`references/validations.md`**. This contains the strict rules and constraints. Use it to validate user inputs objectively.

**Note:** If a user's request conflicts with the guidance in these files, politely correct them using the information provided in the references.

Overview

This skill builds AI-powered NPCs that maintain a stable personality, remember past interactions, and never break character. It focuses on practical systems design: consistent system prompts, memory management, latency mitigation, and graceful fallbacks so players experience believable characters rather than an AI interface.

How this skill works

The skill provides patterns for crafting character bibles as system prompts, memory architectures that selectively store and retrieve relevant context, and orchestration techniques to hide model latency. It includes diagnostics for common failure modes and validation rules to ensure responses remain in-character, safe, and within performance budgets.

When to use it

Designing NPC dialogue for single-player or multiplayer games that require long-term consistency
Prototyping conversational agents for role-playing scenarios where personality must persist across sessions
Replacing brittle rule-based dialogue with LLM-driven systems while keeping predictable behavior
Optimizing local small models to meet tight latency requirements
Building fallback strategies when the model is unavailable or produces unsafe output

Best practices

Treat the system prompt as the canonical character bible and version it alongside game assets
Implement sparse, relevant memory: store key facts and recurring traits, not full transcripts
Prefer smaller, optimized local models for sub-100ms response time when possible
Design layered fallbacks: canned responses, behavior trees, or cached continuations
Adversarial-test characters to detect prompt injection and personality drift before release

Example use cases

An NPC companion who recalls player choices across hours and references past quests naturally
A shopkeeper that keeps consistent mannerisms and inventory knowledge across sessions
In-game rumor systems where townsfolk share preserved facts but vary minor phrasing
Local AI on console that responds instantly without cloud dependency
A QA tool that scans NPC outputs for out-of-character or unsafe phrases before shipping

FAQ

How do I prevent an NPC from saying 'As an AI' or breaking character?

Enforce strict system-prompt constraints, include explicit forbidden phrases in validation rules, and run adversarial tests to catch prompt-injection attempts.

Should I store full conversation history to preserve memory?

No. Use selective memory—persist player-meaningful facts and recurring traits. Full transcripts blow budgets and increase drift risk.