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Skill2.9k repo starsupdated 28d ago

batch-orchestration

Batch orchestration decomposes large-scale code changes into independent units and executes them in parallel using isolated git worktrees and spawning separate agents. Use this Claude Code skill for migrations, refactors, codemods, and similar changes affecting 10 or more files with a consistent pattern across the repository.

Install in Claude Code
Copy
git clone --depth 1 https://github.com/rohitg00/pro-workflow /tmp/batch-orchestration && cp -r /tmp/batch-orchestration/skills/batch-orchestration ~/.claude/skills/batch-orchestration
Then start a new Claude Code session; the skill loads automatically.

SKILL.md

# Batch Orchestration

The `/batch` command pattern for large-scale parallel changes.

## How It Works

```text
/batch <instruction>
  │
  ├── 1. Research: scan repo, understand scope
  ├── 2. Decompose: split into 5-30 independent units
  ├── 3. Present plan: show units, ask for approval
  ├── 4. Execute: one background agent per unit in isolated worktree
  └── 5. Collect: each agent runs tests and opens a PR
```

## Syntax

```bash
/batch Convert all React class components to function components
/batch Add error boundaries to every page component
/batch Migrate from moment.js to dayjs across the codebase
/batch Add OpenTelemetry tracing to all API handlers
```

The instruction should describe the change pattern, not individual files. The batch system finds the files.

## Phase 1: Research

The orchestrator scans the repo to find every instance that matches the instruction:

```bash
grep -r "class.*extends.*Component" --include="*.tsx" -l
```

It builds a complete list of targets and groups them by independence.

## Phase 2: Decompose

Each unit must be:

- **Independent** — no shared state with other units
- **Self-contained** — can be implemented and tested alone
- **Verifiable** — has a clear pass/fail criteria

**Good units:**
```text
Unit 1: Convert src/components/Header.tsx (class → function)
Unit 2: Convert src/components/Footer.tsx (class → function)
Unit 3: Convert src/components/Sidebar.tsx (class → function)
```

**Bad units:**
```text
Unit 1: Convert all components in src/components/ (too broad)
Unit 2: Fix issues from Unit 1 (dependent)
```

Target 5-30 units. Fewer than 5 doesn't justify the overhead. More than 30 and coordination costs grow.

## Phase 3: Plan Approval

The orchestrator presents:

```text
BATCH: Convert class components to function components

Found: 18 class components across src/

Units (18):
  1. src/components/Header.tsx — class Header → function
  2. src/components/Footer.tsx — class Footer → function
  ...
  18. src/pages/Settings.tsx — class Settings → function

Per unit: convert class to function, update hooks, run component tests
Estimated: ~2 min per unit, ~5 min total (parallel)

Proceed? (y/n)
```

**Wait for approval.** Never spawn agents without explicit confirmation.

## Phase 4: Execute

After approval, for each unit:

1. Create isolated git worktree
2. Spawn background agent in that worktree
3. Agent implements the change
4. Agent runs relevant tests
5. Agent opens a PR

Agents run in parallel. Each has its own context window and worktree — no conflicts.

```text
[Agent 1] ── worktree-1 ── Header.tsx ── tests pass ── PR #41
[Agent 2] ── worktree-2 ── Footer.tsx ── tests pass ── PR #42
[Agent 3] ── worktree-3 ── Sidebar.tsx ── tests fail ── flagged
```

## Phase 5: Collect

After all agents complete:

- Summary of pass/fail per unit
- Links to opened PRs
- Any units that failed with error details
- Failed units can be retried individually

## Best For

| Use Case | Why Batch Works |
|----------|-----------------|
| API migrations | Same pattern across many endpoints |
| Dependency upgrades | Find/replace + fix across codebase |
| Codemod-style refactors | Mechanical transformation, file by file |
| Adding instrumentation | Same tracing/logging pattern everywhere |
| Test coverage gaps | Add tests to untested modules independently |
| Lint rule adoption | Apply new rule fixes across all files |

## Anti-Patterns

| Don't Batch | Why |
|-------------|-----|
| Interdependent changes | Units can't run in parallel if they depend on each other |
| Shared state modifications | Multiple agents writing to the same config or state file |
| Architecture changes | Need holistic reasoning, not file-by-file |
| Schema migrations | Database changes must be sequential |
| Changes requiring human judgment per file | Defeats the purpose of automation |

## Relationship to Other Patterns

| Pattern | Scale | Isolation |
|---------|-------|-----------|
| Direct edit | 1-3 files | None needed |
| Subagent | 1 focused task | Forked context |
| Worktree | 1 feature branch | Full repo copy |
| Agent teams | 3-5 parallel tasks | Shared task list |
| **Batch** | 5-30 identical pattern | Full worktree per unit |

Batch is the heaviest tool. Use it when the change is mechanical, repetitive, and the units are truly independent.

## Guardrails

- Always review the decomposition before approving
- Each agent must run tests before opening a PR
- Failed units get flagged, not silently skipped
- Clean up worktrees after all agents complete
- Review PRs in batches — don't merge blindly
agent-teamsSkill

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auto-setupSkill

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bug-captureSkill

Capture a user-reported defect as a durable GitHub issue written in the project's own domain language. Explores the codebase in parallel for context but never leaks file paths or line numbers into the issue. Use when the user reports a bug conversationally, runs a QA pass, or says "file an issue", "log this as a bug", "capture this".

compact-guardSkill

Smart context compaction with state preservation. Saves critical files, task progress, and working state before compaction, restores after. Use before manual compact or when auto-compact triggers.

context-engineerSubagent

Analyzes and optimizes context window usage across sessions. Use when context feels bloated, sessions run slow, or approaching compaction limits.

context-engineeringSkill

Master the four operations of context engineering — Write, Select, Compress, Isolate. Manage token budgets, compaction strategies, and context partitioning to keep AI sessions sharp and efficient.

context-optimizerSkill

Optimize token usage and context management. Use when sessions feel slow, context is degraded, or you're running out of budget.

cost-analystSubagent

Analyze session token usage and cost patterns. Identify expensive operations and recommend optimizations. Use to understand and reduce session costs.