sadd:do-in-parallel

What problem does it solve?

Launching many tasks across files or targets often leads to wasted time and inconsistent results. This Skill orchestrates parallel sub-agents, automatically selecting the best model and applying quality-focused prompting to accelerate batch work while maintaining output quality.

Core Features & Use Cases

• Parallel task dispatch across files or named targets for batch processing of large codebases or data sets
• Unified model selection strategy (opus/sonnet/haiku) to balance quality and cost
• Zero-shot Chain-of-Thought reasoning with mandatory self-critique to improve reliability
• Phase-driven workflow: target identification, task analysis, per-target prompts, self-critique, parallel dispatch, and result collection
• Independence and safety checks to ensure targets can run in parallel without shared state conflicts

Quick Start

Supply a task description and target sources (files or named targets) to initiate parallel sub-agent execution.