
Will Come worked on the Capstone-Projects-2025-Spring/project-003-story-builder-team-1 repository, delivering a robust upgrade to the story-building workflow by enhancing multi-agent orchestration and integrating new chapter and outline tooling. He refactored the agent_routes layer, introduced dynamic agent scaling, and standardized voting endpoints to improve reliability and data integrity. Using TypeScript, Node.js, and LangChain, Will fixed critical issues in LLM-to-tool binding, supervisor logic, and schema definitions, while centralizing streaming logic for maintainability. His work accelerated feature delivery, improved endpoint stability, and provided a more predictable, auditable workflow, demonstrating strong backend development and AI integration skills within a complex system.

April 2025 summary for Capstone-Projects-2025-Spring/project-003-story-builder-team-1: Delivered a robust upgrade to the story-building workflow through enhanced multi-agent orchestration and tool integration. Key features include new agents and endpoints for chapter/outline tooling with per-step tool access, a refactored agent_routes layer with renamed endpoints, and vote-based story steps with dynamic courier-driven agent scaling. Fixed critical reliability issues (LLM-to-tools binding, outdated tool schema, supervisor logic, and endpoint stability) and improved data integrity by standardizing voting endpoints and centralizing streaming logic; updated schemas for outline/chapter tools and moved testing to localhost for faster iteration. These changes improved reliability, scalability, and business value by accelerating feature delivery and providing a more predictable, auditable workflow.
April 2025 summary for Capstone-Projects-2025-Spring/project-003-story-builder-team-1: Delivered a robust upgrade to the story-building workflow through enhanced multi-agent orchestration and tool integration. Key features include new agents and endpoints for chapter/outline tooling with per-step tool access, a refactored agent_routes layer with renamed endpoints, and vote-based story steps with dynamic courier-driven agent scaling. Fixed critical reliability issues (LLM-to-tools binding, outdated tool schema, supervisor logic, and endpoint stability) and improved data integrity by standardizing voting endpoints and centralizing streaming logic; updated schemas for outline/chapter tools and moved testing to localhost for faster iteration. These changes improved reliability, scalability, and business value by accelerating feature delivery and providing a more predictable, auditable workflow.
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