legion:agent-registry

To assemble an AI agent team, you need an agent registry that maps project tasks to agent specialties using semantic and heuristic scoring, ensuring optimal team composition with mandatory review guardrails.

The best way to recommend AI agents is using a recommendation engine that applies semantic and heuristic rankings with metadata boosts, shortlisting candidates against an agent catalog to match specific project intents.

Prevent role conflicts in your AI agent team by enforcing team size limits, mandatory testing and coordination roles, conflict resolution rules, and domain ownership during planning and execution workflows.

Yes, the agent recommendation engine supports spatial computing scenarios alongside design, engineering, testing, product, and marketing workflows by mapping agent personalities to these specific project needs.

Mandatory testing roles are needed in AI team orchestration to enforce coverage guardrails, validate intent-team mappings, and surface missing or redundant agents during the build and review workflows.

Yes, you can use a division-by-division catalog of built-in agents with task-type indexing for gap-analysis workflows to validate intent-team mappings and surface missing or redundant agents.