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AI Agent Configuration

A set of agent behaviors that can be toggled during a session. Each behavior specifies goals, tone, constraints, and switching commands. Behaviors can be combined, and the most recently activated behavior takes precedence on conflicts.

Full Specification#

Reference Index#

A comprehensive configuration covers:

Feature Description
Agent Agent-specific settings, such as name, description, persona, and appearance.
Prompts System, developer, and task prompts that guide the agent’s tone, scope, and response style.
LLM connectors Mapped providers, models, parameters (e.g., temperature, max tokens), and instruction sources.
RAG integrations Connectors to vector stores, retrievers, indexing policies, and grounding strategies.
Behavior and policies Rules for safety, confidentiality, escalation, tool usage, and fallback logic.
Appearance and UX Name, description, persona, response formatting, and icons and color themes
Secrets and credentials Securely referenced tokens, API keys, and connection strings
Metadata Author, version, changelog, licensing, and compliance notes.
Testing and validation Unit tests, prompt regression tests, evaluation metrics, and monitoring hooks.
Operational settings Rate limits, caching, logging, observability, and error-handling policies.

Last updated: 2025-09-28