Thanks — I understand you’re asking how to keep an agent’s personality and rules consistent across multiple tasks when task instances don’t automatically inherit the agent’s instructions. I can help—here are practical, actionable ways to achieve consistency and the questions I need to tailor a solution to your setup. Quick summary of what works • Pass the agent instructions into every task: When you create a task, include the agent’s instructions (for example via

chat_ctx

,

instructions

, or an

extra_instructions

parameter). That ensures each task runs with the same guidance. • Store a shared instruction set and inject it: Keep a single source of truth (a variable, config file, or function that returns the agent’s personality/rules) and reference it whenever you construct agents or tasks. • Use TaskGroup or shared conversation context: Run related tasks inside a

TaskGroup

or a shared context so they can read the same state and user history, reducing divergence between tasks. • Centralize persistent state: Put personality traits, rules, and user-specific preferences in a central store such as

session.userdata

or a

UserData

object so tasks and agent handoffs can read the same values. • Customize prebuilt tasks: For prebuilt tasks (e.g., GetEmailTask, WarmTransferTask), pass

extra_instructions

at initialization to align that task’s behavior with the agent’s personality. Recommended implementation approach (simple, reliable) 1. Create a shared instruction object (string or structured rules). 2. Save it in a central place accessible to your task factory or task constructors. 3. Every time you instantiate a task, include that instruction via the available parameter (e.g.,

instructions

,

chat_ctx

, or

extra_instructions

). 4. Use

TaskGroup

or shared conversation context for multi-step flows so tasks inherit the same conversation-level context and userdata. Questions to make this advice concrete for your system • Which SDK or API are you using to create agents and tasks? (Web, Node, Python, or another) • Are you using prebuilt tasks (like GetEmailTask) or custom task classes? • Do you already have a place where you store session state (e.g.,

session.userdata

) that tasks can access? • Do you want personality/rules to be mutable during a session (updated mid-flow) or fixed for the whole session? If you tell me which language/SDK and whether you use prebuilt tasks or custom tasks, I’ll provide a concise code example showing exactly where to inject the shared instructions and how to structure the shared state so personality and rules remain consistent across agent tasks. Sources: Tasks and task groups | LiveKit Documentation | Context Variables | LiveKit Documentation | Prompting guide | LiveKit Documentation | Agents and handoffs | LiveKit Documentation | Building Multi-Agent Architectures with LiveKit Agents