workflows

name: workflows description: Advanced workflow patterns for Claude Code including Explore-Plan-Code-Commit (E-P-C-C), multi-Claude coordination, parallel development, and iterative refinement loops. Use when planning multi-step implementations or complex engineering tasks.

CLAUDE-workflows.md

Advanced workflow patterns and multi-Claude coordination (Anthropic best practices)

Multi-Claude Coordination

Parallel Review Pattern

Writer Claude: Implements features, writes tests, creates endpoints

Reviewer Claude (parallel): Reviews security, validates coverage, checks patterns

When: Large features, security-sensitive code, complex refactors, pre-production merges

Subtask: Parallel Task Execution

Subtask automates parallel work via Git worktrees. Claude spawns subagents that work concurrently in isolated environments.

subtask draft fix-auth-bug        # Create task for subagent
subtask draft implement-api       # Another parallel task
subtask list                      # Monitor all tasks
subtask fix-auth-bug              # Open TUI for specific task

Workflow:

1. Identify parallelizable work during Plan phase
2. Draft subtasks for each independent piece
3. Subagents execute in separate worktrees
4. Review completed work in TUI
5. Merge or request modifications

Ideal for:

• Multiple independent features
• Parallel bug fixes
• Feature implementation + test writing
• Module-level refactors
• Concurrent code review + implementation

Integration: Use with Ralph loops for iterative parallel work. Deploy code-reviewer on merged results.

Agent Teams (Built-in)

Agent Teams are a built-in Claude Code feature (experimental) that coordinate multiple Claude instances working together. One session acts as the team lead, spawning teammates that work independently and communicate directly.

Enable with CLAUDE_CODE_EXPERIMENTAL_AGENT_TEAMS=1 in settings.json or environment.

# Tell Claude to create a team — it handles spawning and coordination
"Create an agent team to refactor the auth module. Spawn three teammates:
 one for the API layer, one for the database layer, one for tests."

Workflow:

1. Describe the task and team structure to Claude
2. Lead creates shared task list, spawns teammates
3. Teammates work independently, communicate via messages
4. Lead synthesizes results, coordinates merges
5. Clean up: ask the lead to shut down teammates and clean up

Controls:

• Shift+Up/Down — cycle between teammates (in-process mode)
• Shift+Tab — toggle delegate mode (lead coordinates only, no coding)
• Ctrl+T — toggle task list
• Escape — interrupt a teammate's current turn

Best use cases:

• Research and review (multiple reviewers, different lenses)
• New modules or features (each teammate owns a piece)
• Debugging with competing hypotheses (parallel investigation)
• Cross-layer coordination (frontend + backend + tests)

Not ideal for:

• Sequential tasks with dependencies
• Same-file edits (causes overwrites)
• Simple tasks (coordination overhead exceeds benefit)

vs Subtask: Agent teams are built-in and support inter-agent communication. Subtask uses isolated git worktrees with a CLI. Use agent teams when teammates need to discuss and coordinate; use Subtask when tasks are fully independent and you want file isolation.

vs Subagents: Subagents run within a single session and report back. Agent teams are separate sessions that communicate peer-to-peer. Use subagents for quick, focused research; use agent teams for complex collaborative work.

Hooks for quality gates:

• TeammateIdle — runs when a teammate finishes. Exit code 2 sends feedback and keeps them working.
• TaskCompleted — runs when a task is marked complete. Exit code 2 blocks completion with feedback.

Git Worktrees (Manual)

For manual worktree management without Subtask:

git worktree add .worktrees/feature-xyz feature-xyz
git worktree add .worktrees/fix-auth-bug fix-auth-bug
git worktree list
git worktree remove .worktrees/feature-xyz
git worktree prune

Use for: Non-overlapping components, migrations, parallel experiments

When Multiple Sessions

Subagent Strategy

"Preserve context without losing efficiency" — Anthropic

Deploy subagents early and often to preserve main context.

Use for: Exploration, pattern discovery, verification, parallel investigations, detail-gathering

Keep in main: Tasks needing history, final implementations, direct Q&A, architecture decisions

Available Types

Patterns

Explore → Plan → Implement:

1. Deploy Explore agent → Find patterns, integration points
2. Deploy Plan agent → Generate architecture plan
3. Review with user → Get approval
4. Implement in main → Execute plan

Parallel Investigation: Deploy 3+ agents simultaneously (check commits, analyze logs, search issues), synthesize in main

Context Preservation: Don't pollute main with tangential investigation. Deploy agent, get findings, continue main work.

Best Practices

• Deploy BEFORE consuming context with exploration
• Launch multiple agents in parallel (single tool call)
• Resume agents for follow-ups (preserves context)
• Use run_in_background: true for long tasks
• Specify thoroughness: quick/medium/very thorough

Primary Workflow: Explore-Plan-Code-Commit

"Steps #1-#2 are crucial—without them, Claude jumps straight to coding" — Anthropic

Phase 1: Explore (DON'T CODE)

Actions: Read files, deploy Explore subagent, search with rg, check CLAUDE-patterns.md, review activeContext

Exit: Understand existing code, patterns, changes needed, dependencies

Phase 2: Plan (THINK FIRST)

Actions: Use sequential-thinking for complex decisions, create TodoWrite plan, deploy Plan agent if needed, present for approval

Exit: Plan documented, user approved, files identified, dependencies clear, clarification gate passed (see CLAUDE-specgates.md)

Phase 3: Code

Actions: Implement per plan, track with TodoWrite, use Gemini-CLI for boilerplate, Context7 for docs, verify with build

Exit: All todos complete, build passes, solution verified

Phase 4: Commit

Actions: Pre-commit review (Gemini-CLI/CodeRabbit), conventional commit format, update memory bank, deploy to Vercel, document solutions

Exit: Code reviewed, committed, deployed, documented

TDD Workflow

1. Write tests (expected inputs/outputs)
2. Confirm tests fail (red)
3. Commit tests
4. Implement until tests pass (green)
5. Refactor and optimize
6. Verify all tests pass

Ralph Loop Workflow

Continuous iteration until completion criteria met. See RALPH-LOOPS.md for full guide.

When: TDD, build fixes, API implementations, long-running features, migrations, quality improvements

Not for: Frequent design decisions, ambiguous requirements, production debugging

Process:

1. Define clear completion criteria (tests pass, build succeeds)
2. Set safety parameters (max iterations)
3. Iterate: implement → verify → analyze → iterate
4. Signal completion when criteria met

Max iterations: Simple 10-15, Medium 15-25, Complex 25-40

Integration: Use in Code phase of Explore-Plan-Code-Commit

Visual Iteration Workflow

1. Receive design mock/screenshot
2. Generate (v0 or Figma tools)
3. Screenshot result
4. Compare and iterate
5. Refine until match

"Claude's outputs improve significantly with iteration" — Anthropic

Checklist-Driven Migrations

For large-scale changes (deps, APIs, refactors):

1. Generate checklist of affected areas
2. Use TodoWrite as scratchpad
3. Address systematically
4. Mark completion after verification

Context Management

When to /clear

• After completing features
• Switching to unrelated tasks
• Before large refactors
• Unfocused conversation

Don't Clear

• Mid-task
• User might reference history
• Architecture decisions need context

Alternative: Deploy subagent for tangential tasks instead of polluting main

Interactive Collaboration

Controls: Escape (interrupt), Double-Escape (alternatives), Request undo, Ask questions

Rules:

• Plan first, course correct as needed
• Ask when ambiguous
• Present options for decisions
• Checkpoint at milestones
• Never fully autonomous large changes
• Never assume intent without confirmation

Specificity improves results: Detailed prompts → better first attempts

Data Input Strategies

Git Integration

History Analysis

git log -p -- src/auth/ | head -500    # Why?
git log --all --grep="auth" --oneline   # When?

Complex Operations

• Interactive rebases: Provide list, get plan
• Merge conflicts: Share markers, get resolution
• Commit messages: Generate from git diff --staged
• Cherry-picking: Identify and apply

GitHub CLI

gh pr create --title "feat: JWT" --body "$(git log main..HEAD --format='- %s')"
gh pr view 123 --comments
gh pr create --reviewer @security-team
git commit -m "fix: auth bug (fixes #123)"

Workflow Decision Matrix

Key Takeaways

1. Plan before coding — Exploration prevents wasted effort
2. Subagents early — Preserve main context
3. Clear context frequently — Maintain focus
4. Parallel sessions for quality — Writer + Reviewer
5. Iterate with user — Collaboration over autonomy (except Ralph)
6. Ralph loops for iteration — Autonomous on well-defined tasks
7. Specific prompts — Detail improves first-attempt success
8. Mix input methods — Right tool for each data type
9. Leverage git history — Answer architectural questions
10. Subtask for parallelism — Multiple independent tasks in isolated worktrees
11. Agent teams for collaboration — When teammates need to communicate, not just report back

Project-Specific Workflows

Updated: 2026-02-10 | Source: Anthropic Best Practices, Agent Teams Docs