intent-detection

Agent routing uses natural language input analysis to identify user intent and direct tasks to the appropriate specialist agent, preventing context loss. It matches keywords, file patterns, and action verbs against a centralized trigger registry.

Confidence-based execution in intent classification automatically executes high-confidence tasks, requests user confirmation for medium-confidence matches, and presents alternative options for ambiguous inputs. This prevents misrouting by validating uncertain intent matches.

Semantic routing is a mechanism that scores and selects the optimal agent for a task using keyword, action, and file-pattern matching. You need it for workflow orchestration when managing multi-agent systems to prevent fragmentation and context loss.

Intent detection operates across software engineering, infrastructure, and management domains by analyzing natural language input. It identifies user intent and routes tasks to the appropriate specialist agent or skill module within these specified categories.

The best way to handle ambiguous inputs in agent orchestration is using confidence-based decision logic that presents alternative options. This logic evaluates intent matches and only auto-executes high-confidence tasks while requesting confirmation for uncertain ones.

Multi-agent systems lose context during manual switching due to fragmentation. Automatic intent detection solves this by analyzing user input to determine the correct specialist agent or workflow, ensuring seamless routing without context loss.