What problem does it solve?
Orchestrating multi-step AI workflows where each step's output feeds into the next can be complex and error-prone. This skill simplifies the creation of sequential processing pipelines, ensuring seamless data flow and context preservation across agents.
Core Features & Use Cases
- Custom Chains: Define and execute custom sequences of prompts for maximum flexibility.
- Predefined Pipelines: Utilize battle-tested workflows for common tasks like analysis, refactoring, testing, and optimization.
- Context Preservation: Each step receives the complete output from the previous step, maintaining full context.
- Use Case: Need to refactor a codebase? Use the
refactor pipeline to first identify code smells, then create a refactoring plan, and finally apply changes to high-priority items, all in an automated, sequential flow.
Quick Start
Run a custom chain to analyze codebase structure, identify improvement areas, and generate an action plan.
claude-flow stream-chain run "Analyze codebase structure" "Identify improvement areas" "Generate action plan"