home / skills / a5c-ai / babysitter / lag-compensation
/plugins/babysitter/skills/babysit/process/specializations/game-development/skills/lag-compensation
This skill helps implement lag compensation techniques for reliable client-side prediction and rollback in networked applications.
npx playbooks add skill a5c-ai/babysitter --skill lag-compensationReview the files below or copy the command above to add this skill to your agents.
---
name: lag-compensation
description: Lag compensation skill for client-side prediction and rollback.
allowed-tools: Read, Grep, Write, Bash, Edit, Glob, WebFetch
---
# Lag Compensation Skill
Network lag compensation techniques.
## Capabilities
- Client-side prediction
- Server reconciliation
- Rollback netcode
- Hitbox rewinding
This skill implements lag compensation techniques for real-time systems, focused on client-side prediction, server reconciliation, rollback netcode, and hitbox rewinding. It provides deterministic, resumable mechanics that make interactive applications tolerant to network latency and jitter. The skill is implemented in JavaScript and designed to integrate into agentic workflows that require trustworthy, reproducible state management.
The skill maintains a deterministic simulation timeline that both client and server can reference. Clients perform local prediction to hide latency, send input frames to the server, and apply server reconciliation when authoritative state arrives. For fast-paced interactions, rollback netcode rewinds and re-simulates frames based on corrected inputs. Hitbox rewinding lets the server validate collision events against historical states to preserve fairness.
Does this skill require a specific transport layer?
No. The techniques are transport-agnostic but benefit from reliable, ordered delivery for authoritative state and occasional UDP-style packets for low-latency input.
How far back should I allow rollbacks?
Choose a window based on expected latency and resource constraints. Typical windows range from 100–500 ms, but profile CPU and memory to set practical limits.