| name | orchestrate-batch-refactor |
| description | Plan and execute large refactors with dependency-aware work packets and parallel analysis. |
| type | skill |
| created | 2026-02-27T00:00:00.000Z |
| domain | cloud-infrastructure |
| category | azure |
| risk | safe |
| source | Dimillian/Skills (MIT) |
| tags | ["skill","cloud-infrastructure","azure","orchestrate","batch","refactor"] |
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.
When to Use
- When a refactor spans many files or subsystems and needs clear work partitioning.
- When you need dependency-aware planning before parallel implementation.
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
- Define scope and success criteria.
- List target paths/modules and non-goals.
- State behavior constraints (for example: preserve external behavior).
- 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.
- 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.
- 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.
- Integrate and verify.
- Review packet outputs, resolve overlaps, and run validation gates.
- Run targeted tests per packet, then broader suite for integrated scope.
- Report and close.
- Summarize packet outcomes, key refactors, conflicts resolved, and residual risks.
Work Packet Rules
- One owner per file per execution wave.
- No parallel edits on overlapping file sets.
- Keep packet goals narrow and measurable.
- Include explicit done criteria and required checks.
- Prefer behavior-preserving refactors unless user explicitly requests behavior change.
