Orchestrate Batch Refactor

Overview

Use this skill to run high-throughput refactors safely. Analyze scope in parallel, synthesize a single plan, then execute independent work packets with sub-agents.

Inputs

• Repo path and target scope (paths, modules, or feature area)
• Goal type: refactor, rewrite, or hybrid
• Constraints: behavior parity, API stability, deadlines, test requirements

When to Use Parallelization

• Use this skill for medium/large scope touching many files or subsystems.
• Skip multi-agent execution for tiny edits or highly coupled single-file work.

Core Workflow

1. Define scope and success criteria.
   • List target paths/modules and non-goals.
   • State behavior constraints (for example: preserve external behavior).
2. Run parallel analysis first.
   • Split target scope into analysis lanes.
   • Spawn explorer sub-agents in parallel to analyze each lane.
   • Ask each agent for: intent map, coupling risks, candidate work packets, required validations.
3. Build one dependency-aware plan.
   • Merge explorer output into a single work graph.
   • Create work packets with clear file ownership and validation commands.
   • Sequence packets by dependency level; run only independent packets in parallel.
4. Execute with worker agents.
   • Spawn one worker per independent packet.
   • Assign explicit ownership (files/responsibility).
   • Instruct every worker that they are not alone in the codebase and must ignore unrelated edits.
5. Integrate and verify.
   • Review packet outputs, resolve overlaps, and run validation gates.
   • Run targeted tests per packet, then broader suite for integrated scope.
6. Report and close.
   • Summarize packet outcomes, key refactors, conflicts resolved, and residual risks.

Work Packet Rules