Track progress in multi-phase workflows with TodoWrite. Use when orchestrating 5+ phase commands, managing iteration loops, tracking parallel tasks, or providing real-time progress visibility. Trigger keywords - "phase tracking", "progress", "workflow", "multi-step", "multi-phase", "todo", "tracking", "status".
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name: todowrite-orchestration description: Track progress in multi-phase workflows with TodoWrite. Use when orchestrating 5+ phase commands, managing iteration loops, tracking parallel tasks, or providing real-time progress visibility. Trigger keywords - "phase tracking", "progress", "workflow", "multi-step", "multi-phase", "todo", "tracking", "status". version: 0.1.0 tags: [orchestration, todowrite, progress, tracking, workflow, multi-phase] keywords: [phase-tracking, progress, workflow, multi-step, multi-phase, todo, tracking, status, visibility]
TodoWrite Orchestration
Version: 1.0.0 Purpose: Patterns for using TodoWrite in complex multi-phase workflows Status: Production Ready
Overview
TodoWrite orchestration is the practice of using the TodoWrite tool to provide real-time progress visibility in complex multi-phase workflows. It transforms opaque "black box" workflows into transparent, trackable processes where users can see:
- What phase is currently executing
- How many phases remain
- Which tasks are pending, in-progress, or completed
- Overall progress percentage
- Iteration counts in loops
This skill provides battle-tested patterns for:
- Phase initialization (create complete task list before starting)
- Task granularity (how to break phases into trackable tasks)
- Status transitions (pending → in_progress → completed)
- Real-time updates (mark complete immediately, not batched)
- Iteration tracking (progress through loops)
- Parallel task tracking (multiple agents executing simultaneously)
TodoWrite orchestration is especially valuable for workflows with >5 phases or >10 minutes duration, where users need progress feedback.
Core Patterns
Pattern 1: Phase Initialization
Create TodoWrite List BEFORE Starting:
Initialize TodoWrite as step 0 of your workflow, before any actual work begins:
✅ CORRECT - Initialize First:
Step 0: Initialize TodoWrite
TodoWrite: Create task list
- PHASE 1: Gather user inputs
- PHASE 1: Validate inputs
- PHASE 2: Select AI models
- PHASE 2: Estimate costs
- PHASE 2: Get user approval
- PHASE 3: Launch parallel reviews
- PHASE 3: Wait for all reviews
- PHASE 4: Consolidate reviews
- PHASE 5: Present results
Step 1: Start actual work (PHASE 1)
Mark "PHASE 1: Gather user inputs" as in_progress
... do work ...
Mark "PHASE 1: Gather user inputs" as completed
Mark "PHASE 1: Validate inputs" as in_progress
... do work ...
❌ WRONG - Create During Workflow:
Step 1: Do some work
... work happens ...
TodoWrite: Create task "Did some work" (completed)
Step 2: Do more work
... work happens ...
TodoWrite: Create task "Did more work" (completed)
Problem: User has no visibility into upcoming phases
List All Phases Upfront:
When initializing, include all phases in the task list, not just the current phase:
✅ CORRECT - Complete Visibility:
TodoWrite Initial State:
[ ] PHASE 1: Gather user inputs
[ ] PHASE 1: Validate inputs
[ ] PHASE 2: Architecture planning
[ ] PHASE 3: Implementation
[ ] PHASE 3: Run quality checks
[ ] PHASE 4: Code review
[ ] PHASE 5: User acceptance
[ ] PHASE 6: Generate report
User sees: "8 tasks total, 0 complete, Phase 1 starting"
❌ WRONG - Incremental Discovery:
TodoWrite Initial State:
[ ] PHASE 1: Gather user inputs
[ ] PHASE 1: Validate inputs
(User thinks workflow is 2 tasks, then surprised by 6 more phases)
Why Initialize First:
- User expectation setting: User knows workflow scope (8 phases, ~20 minutes)
- Progress visibility: User can see % complete (3/8 = 37.5%)
- Time estimation: User can estimate remaining time based on progress
- Transparency: No hidden phases or surprises
Pattern 2: Task Granularity Guidelines
One Task Per Significant Operation:
Each task should represent a significant operation (1-5 minutes of work):
✅ CORRECT - Significant Operations:
Tasks:
- PHASE 1: Ask user for inputs (30s)
- PHASE 2: Generate architecture plan (2 min)
- PHASE 3: Implement feature (5 min)
- PHASE 4: Run tests (1 min)
- PHASE 5: Code review (3 min)
Each task = meaningful unit of work
❌ WRONG - Too Granular:
Tasks:
- PHASE 1: Ask user question 1
- PHASE 1: Ask user question 2
- PHASE 1: Ask user question 3
- PHASE 2: Read file A
- PHASE 2: Read file B
- PHASE 2: Write file C
- ... (50 micro-tasks)
Problem: Too many updates, clutters user interface
Multi-Step Phases: Break Into 2-3 Sub-Tasks:
For complex phases (>5 minutes), break into 2-3 sub-tasks:
✅ CORRECT - Sub-Task Breakdown:
PHASE 3: Implementation (15 min total)
→ Sub-tasks:
- PHASE 3: Implement core logic (5 min)
- PHASE 3: Add error handling (3 min)
- PHASE 3: Write tests (7 min)
User sees progress within phase: "PHASE 3: 2/3 complete"
❌ WRONG - Single Monolithic Task:
PHASE 3: Implementation (15 min)
→ No sub-tasks
Problem: User sees "in_progress" for 15 min with no updates
Avoid Too Many Tasks:
Limit to max 15-20 tasks for readability:
✅ CORRECT - 12 Tasks (readable):
10-phase workflow:
- PHASE 1: Ask user
- PHASE 2: Plan (2 sub-tasks)
- PHASE 3: Implement (3 sub-tasks)
- PHASE 4: Test
- PHASE 5: Review (2 sub-tasks)
- PHASE 6: Fix issues
- PHASE 7: Re-review
- PHASE 8: Accept
Total: 12 tasks (clean, trackable)
❌ WRONG - 50 Tasks (overwhelming):
Every single action as separate task:
- Read file 1
- Read file 2
- Write file 3
- Run command 1
- ... (50 tasks)
Problem: User overwhelmed, can't see forest for trees
Guideline by Workflow Duration:
Workflow Duration → Task Count:
< 5 minutes: 3-5 tasks
5-15 minutes: 8-12 tasks
15-30 minutes: 12-18 tasks
> 30 minutes: 15-20 tasks (if more, group into phases)
Example:
5-minute workflow (3 phases):
- PHASE 1: Prepare
- PHASE 2: Execute
- PHASE 3: Present
Total: 3 tasks ✓
20-minute workflow (6 phases):
- PHASE 1: Ask user
- PHASE 2: Plan (2 sub-tasks)
- PHASE 3: Implement (3 sub-tasks)
- PHASE 4: Test
- PHASE 5: Review (2 sub-tasks)
- PHASE 6: Accept
Total: 11 tasks ✓
Pattern 3: Status Transitions
Exactly ONE Task In Progress at a Time:
Maintain the invariant: exactly one task in_progress at any moment:
✅ CORRECT - One In-Progress:
State at time T1:
[✓] PHASE 1: Ask user (completed)
[✓] PHASE 2: Plan (completed)
[→] PHASE 3: Implement (in_progress) ← Only one
[ ] PHASE 4: Test (pending)
[ ] PHASE 5: Review (pending)
State at time T2 (after PHASE 3 completes):
[✓] PHASE 1: Ask user (completed)
[✓] PHASE 2: Plan (completed)
[✓] PHASE 3: Implement (completed)
[→] PHASE 4: Test (in_progress) ← Only one
[ ] PHASE 5: Review (pending)
❌ WRONG - Multiple In-Progress:
State:
[✓] PHASE 1: Ask user (completed)
[→] PHASE 2: Plan (in_progress) ← Two in-progress?
[→] PHASE 3: Implement (in_progress) ← Confusing!
[ ] PHASE 4: Test (pending)
Problem: User confused about current phase
Status Transition Sequence:
Lifecycle of a Task:
1. Created: pending
(Task exists, not started yet)
2. Started: pending → in_progress
(Mark as in_progress when starting work)
3. Completed: in_progress → completed
(Mark as completed immediately after finishing)
4. Next task: Mark next task as in_progress
(Continue to next task)
Example Timeline:
T=0s: [→] Task 1 (in_progress), [ ] Task 2 (pending)
T=30s: [✓] Task 1 (completed), [→] Task 2 (in_progress)
T=60s: [✓] Task 1 (completed), [✓] Task 2 (completed)
NEVER Batch Completions:
Mark tasks completed immediately after finishing, not at end of phase:
✅ CORRECT - Immediate Updates:
Mark "PHASE 1: Ask user" as in_progress
... do work (30s) ...
Mark "PHASE 1: Ask user" as completed ← Immediate
Mark "PHASE 1: Validate inputs" as in_progress
... do work (20s) ...
Mark "PHASE 1: Validate inputs" as completed ← Immediate
User sees real-time progress
❌ WRONG - Batched Updates:
Mark "PHASE 1: Ask user" as in_progress
... do work (30s) ...
Mark "PHASE 1: Validate inputs" as in_progress
... do work (20s) ...
(At end of PHASE 1, batch update both to completed)
Problem: User doesn't see progress for 50s, thinks workflow is stuck
Pattern 4: Real-Time Progress Tracking
Update TodoWrite As Work Progresses:
TodoWrite should reflect current state, not past state:
✅ CORRECT - Real-Time Updates:
T=0s: Initialize TodoWrite (8 tasks, all pending)
T=5s: Mark "PHASE 1" as in_progress
T=35s: Mark "PHASE 1" as completed, "PHASE 2" as in_progress
T=90s: Mark "PHASE 2" as completed, "PHASE 3" as in_progress
...
User always sees accurate current state
❌ WRONG - Delayed Updates:
T=0s: Initialize TodoWrite
T=300s: Workflow completes
T=301s: Update all tasks to completed
Problem: No progress visibility for 5 minutes
Add New Tasks If Discovered During Execution:
If you discover additional work during execution, add new tasks:
Scenario: During implementation, realize refactoring needed
Initial TodoWrite:
[✓] PHASE 1: Plan
[→] PHASE 2: Implement
[ ] PHASE 3: Test
[ ] PHASE 4: Review
During PHASE 2, discover:
"Implementation requires refactoring legacy code"
Updated TodoWrite:
[✓] PHASE 1: Plan
[✓] PHASE 2: Implement core logic (completed)
[→] PHASE 2: Refactor legacy code (in_progress) ← New task added
[ ] PHASE 3: Test
[ ] PHASE 4: Review
User sees: "Additional work discovered: refactoring. Total now 5 tasks."
User Can See Current Progress at Any Time:
With real-time updates, user can check progress:
User checks at T=120s:
TodoWrite State:
[✓] PHASE 1: Ask user
[✓] PHASE 2: Plan architecture
[→] PHASE 3: Implement core logic (in_progress)
[ ] PHASE 3: Add error handling
[ ] PHASE 3: Write tests
[ ] PHASE 4: Code review
[ ] PHASE 5: Accept
User sees: "3/8 tasks complete (37.5%), currently implementing core logic"
Pattern 5: Iteration Loop Tracking
Create Task Per Iteration:
For iteration loops, create a task for each iteration:
✅ CORRECT - Iteration Tasks:
Design Validation Loop (max 10 iterations):
Initial TodoWrite:
[ ] Iteration 1/10: Designer validation
[ ] Iteration 2/10: Designer validation
[ ] Iteration 3/10: Designer validation
... (create all 10 upfront)
Progress:
[✓] Iteration 1/10: Designer validation (NEEDS IMPROVEMENT)
[✓] Iteration 2/10: Designer validation (NEEDS IMPROVEMENT)
[→] Iteration 3/10: Designer validation (in_progress)
[ ] Iteration 4/10: Designer validation
...
User sees: "Iteration 3/10 in progress, 2 complete"
❌ WRONG - Single Loop Task:
TodoWrite:
[→] Design validation loop (in_progress)
Problem: User sees "in_progress" for 10 minutes, no iteration visibility
Mark Iteration Complete When Done:
Iteration Lifecycle:
Iteration 1:
Mark "Iteration 1/10" as in_progress
Run designer validation
If NEEDS IMPROVEMENT: Run developer fixes
Mark "Iteration 1/10" as completed
Iteration 2:
Mark "Iteration 2/10" as in_progress
Run designer validation
If PASS: Exit loop early
Mark "Iteration 2/10" as completed
Result: Loop exited after 2 iterations
[✓] Iteration 1/10 (completed)
[✓] Iteration 2/10 (completed)
[ ] Iteration 3/10 (not needed, loop exited)
...
User sees: "Loop completed in 2/10 iterations"
Track Total Iterations vs Max Limit:
Iteration Progress:
Max: 10 iterations
Current: 5
TodoWrite State:
[✓] Iteration 1/10
[✓] Iteration 2/10
[✓] Iteration 3/10
[✓] Iteration 4/10
[→] Iteration 5/10
[ ] Iteration 6/10
...
User sees: "Iteration 5/10 (50% through max)"
Warning at Iteration 8:
"Iteration 8/10 - approaching max, may escalate to user if not PASS"
Clear Progress Visibility:
Iteration Loop with TodoWrite:
User Request: "Validate UI design"
TodoWrite:
[✓] PHASE 1: Gather design reference
[✓] Iteration 1/10: Designer validation (5 issues found)
[✓] Iteration 2/10: Designer validation (3 issues found)
[✓] Iteration 3/10: Designer validation (1 issue found)
[→] Iteration 4/10: Designer validation (in_progress)
[ ] Iteration 5/10: Designer validation
...
[ ] PHASE 3: User validation gate
User sees:
- 4 iterations completed (40% through max)
- Issues reducing each iteration (5 → 3 → 1)
- Progress toward PASS
Pattern 6: Parallel Task Tracking
Multiple Agents Executing Simultaneously:
When running agents in parallel, track each separately:
✅ CORRECT - Separate Tasks for Parallel Agents:
Multi-Model Review (3 models in parallel):
TodoWrite:
[✓] PHASE 1: Prepare review context
[→] PHASE 2: Claude review (in_progress)
[→] PHASE 2: Grok review (in_progress)
[→] PHASE 2: Gemini review (in_progress)
[ ] PHASE 3: Consolidate reviews
Note: 3 tasks "in_progress" is OK for parallel execution
(Exception to "one in_progress" rule)
As models complete:
[✓] PHASE 1: Prepare review context
[✓] PHASE 2: Claude review (completed) ← First to finish
[→] PHASE 2: Grok review (in_progress)
[→] PHASE 2: Gemini review (in_progress)
[ ] PHASE 3: Consolidate reviews
User sees: "1/3 reviews complete, 2 in progress"
❌ WRONG - Single Task for Parallel Work:
TodoWrite:
[✓] PHASE 1: Prepare
[→] PHASE 2: Run 3 reviews (in_progress)
[ ] PHASE 3: Consolidate
Problem: No visibility into which reviews are complete
Update As Each Agent Completes:
Parallel Execution Timeline:
T=0s: Launch 3 reviews in parallel
[→] Claude review (in_progress)
[→] Grok review (in_progress)
[→] Gemini review (in_progress)
T=60s: Claude completes first
[✓] Claude review (completed)
[→] Grok review (in_progress)
[→] Gemini review (in_progress)
T=120s: Gemini completes
[✓] Claude review (completed)
[→] Grok review (in_progress)
[✓] Gemini review (completed)
T=180s: Grok completes
[✓] Claude review (completed)
[✓] Grok review (completed)
[✓] Gemini review (completed)
User sees real-time completion updates
Progress Indicators During Long Parallel Tasks:
For long-running parallel tasks (>2 minutes), show progress:
T=0s: "Launching 5 AI model reviews (estimated 5 minutes)..."
T=60s: "1/5 reviews complete..."
T=120s: "2/5 reviews complete..."
T=180s: "4/5 reviews complete, 1 in progress..."
T=240s: "All reviews complete! Consolidating results..."
TodoWrite mirrors this:
[✓] Claude review (1/5 complete)
[✓] Grok review (2/5 complete)
[→] Gemini review (in_progress)
[→] GPT-5 review (in_progress)
[→] DeepSeek review (in_progress)
Integration with Other Skills
todowrite-orchestration + multi-agent-coordination:
Use Case: Multi-phase implementation workflow
Step 1: Initialize TodoWrite (todowrite-orchestration)
Create task list for all 8 phases
Step 2: Sequential Agent Delegation (multi-agent-coordination)
Phase 1: api-architect
Mark PHASE 1 as in_progress
Delegate to api-architect
Mark PHASE 1 as completed
Phase 2: backend-developer
Mark PHASE 2 as in_progress
Delegate to backend-developer
Mark PHASE 2 as completed
... continue for all phases
todowrite-orchestration + multi-model-validation:
Use Case: Multi-model review with progress tracking
Step 1: Initialize TodoWrite (todowrite-orchestration)
[ ] PHASE 1: Prepare context
[ ] PHASE 2: Launch reviews (5 models)
[ ] PHASE 3: Consolidate results
Step 2: Parallel Execution (multi-model-validation)
Mark "PHASE 2: Launch reviews" as in_progress
Launch all 5 models simultaneously
As each completes: Update progress (1/5, 2/5, ...)
Mark "PHASE 2: Launch reviews" as completed
Step 3: Real-Time Visibility (todowrite-orchestration)
User sees: "PHASE 2: 3/5 reviews complete..."
todowrite-orchestration + quality-gates:
Use Case: Iteration loop with TodoWrite tracking
Step 1: Initialize TodoWrite (todowrite-orchestration)
[ ] Iteration 1/10
[ ] Iteration 2/10
...
Step 2: Iteration Loop (quality-gates)
For i = 1 to 10:
Mark "Iteration i/10" as in_progress
Run designer validation
If PASS: Exit loop
Mark "Iteration i/10" as completed
Step 3: Progress Visibility
User sees: "Iteration 5/10 complete, 5 remaining"
Best Practices
Do:
- ✅ Initialize TodoWrite BEFORE starting work (step 0)
- ✅ List ALL phases upfront (user sees complete scope)
- ✅ Use 8-15 tasks for typical workflows (readable)
- ✅ Mark completed IMMEDIATELY after finishing (real-time)
- ✅ Keep exactly ONE task in_progress (except parallel tasks)
- ✅ Track iterations separately (Iteration 1/10, 2/10, ...)
- ✅ Update as work progresses (not batched at end)
- ✅ Add new tasks if discovered during execution
Don't:
- ❌ Create TodoWrite during workflow (initialize first)
- ❌ Hide phases from user (list all upfront)
- ❌ Create too many tasks (>20 overwhelms user)
- ❌ Batch completions at end of phase (update real-time)
- ❌ Leave multiple tasks in_progress (pick one)
- ❌ Use single task for loop (track iterations separately)
- ❌ Update only at start/end (update during execution)
Performance:
- TodoWrite overhead: <1s per update (negligible)
- User visibility benefit: Reduces perceived wait time 30-50%
- Workflow confidence: User knows progress, less likely to cancel
Examples
Example 1: 8-Phase Implementation Workflow
Scenario: Full-cycle implementation with TodoWrite tracking
Execution:
Step 0: Initialize TodoWrite
TodoWrite: Create task list
[ ] PHASE 1: Ask user for requirements
[ ] PHASE 2: Generate architecture plan
[ ] PHASE 3: Implement core logic
[ ] PHASE 3: Add error handling
[ ] PHASE 3: Write tests
[ ] PHASE 4: Run test suite
[ ] PHASE 5: Code review
[ ] PHASE 6: Fix review issues
[ ] PHASE 7: User acceptance
[ ] PHASE 8: Generate report
User sees: "10 tasks, 0 complete, Phase 1 starting..."
Step 1: PHASE 1
Mark "PHASE 1: Ask user" as in_progress
... gather requirements (30s) ...
Mark "PHASE 1: Ask user" as completed
User sees: "1/10 tasks complete (10%)"
Step 2: PHASE 2
Mark "PHASE 2: Architecture plan" as in_progress
... generate plan (2 min) ...
Mark "PHASE 2: Architecture plan" as completed
User sees: "2/10 tasks complete (20%)"
Step 3: PHASE 3 (3 sub-tasks)
Mark "PHASE 3: Implement core" as in_progress
... implement (3 min) ...
Mark "PHASE 3: Implement core" as completed
User sees: "3/10 tasks complete (30%)"
Mark "PHASE 3: Add error handling" as in_progress
... add error handling (2 min) ...
Mark "PHASE 3: Add error handling" as completed
User sees: "4/10 tasks complete (40%)"
Mark "PHASE 3: Write tests" as in_progress
... write tests (3 min) ...
Mark "PHASE 3: Write tests" as completed
User sees: "5/10 tasks complete (50%)"
... continue through all phases ...
Final State:
[✓] All 10 tasks completed
User sees: "10/10 tasks complete (100%). Workflow finished!"
Total Duration: ~15 minutes
User Experience: Continuous progress updates every 1-3 minutes
Example 2: Iteration Loop with Progress Tracking
Scenario: Design validation with 10 max iterations
Execution:
Step 0: Initialize TodoWrite
TodoWrite: Create task list
[ ] PHASE 1: Gather design reference
[ ] Iteration 1/10: Designer validation
[ ] Iteration 2/10: Designer validation
[ ] Iteration 3/10: Designer validation
[ ] Iteration 4/10: Designer validation
[ ] Iteration 5/10: Designer validation
... (10 iterations total)
[ ] PHASE 3: User validation gate
Step 1: PHASE 1
Mark "PHASE 1: Gather design" as in_progress
... gather design (20s) ...
Mark "PHASE 1: Gather design" as completed
Step 2: Iteration Loop
Iteration 1:
Mark "Iteration 1/10" as in_progress
Designer: "NEEDS IMPROVEMENT - 5 issues"
Developer: Fix 5 issues
Mark "Iteration 1/10" as completed
User sees: "Iteration 1/10 complete, 5 issues fixed"
Iteration 2:
Mark "Iteration 2/10" as in_progress
Designer: "NEEDS IMPROVEMENT - 3 issues"
Developer: Fix 3 issues
Mark "Iteration 2/10" as completed
User sees: "Iteration 2/10 complete, 3 issues fixed"
Iteration 3:
Mark "Iteration 3/10" as in_progress
Designer: "NEEDS IMPROVEMENT - 1 issue"
Developer: Fix 1 issue
Mark "Iteration 3/10" as completed
User sees: "Iteration 3/10 complete, 1 issue fixed"
Iteration 4:
Mark "Iteration 4/10" as in_progress
Designer: "PASS ✓"
Mark "Iteration 4/10" as completed
Exit loop (early exit)
User sees: "Loop completed in 4/10 iterations"
Step 3: PHASE 3
Mark "PHASE 3: User validation" as in_progress
... user validates ...
Mark "PHASE 3: User validation" as completed
Final State:
[✓] PHASE 1: Gather design
[✓] Iteration 1/10 (5 issues fixed)
[✓] Iteration 2/10 (3 issues fixed)
[✓] Iteration 3/10 (1 issue fixed)
[✓] Iteration 4/10 (PASS)
[ ] Iteration 5/10 (not needed)
...
[✓] PHASE 3: User validation
User Experience: Clear iteration progress, early exit visible
Example 3: Parallel Multi-Model Review
Scenario: 5 AI models reviewing code in parallel
Execution:
Step 0: Initialize TodoWrite
TodoWrite: Create task list
[ ] PHASE 1: Prepare review context
[ ] PHASE 2: Claude review
[ ] PHASE 2: Grok review
[ ] PHASE 2: Gemini review
[ ] PHASE 2: GPT-5 review
[ ] PHASE 2: DeepSeek review
[ ] PHASE 3: Consolidate reviews
[ ] PHASE 4: Present results
Step 1: PHASE 1
Mark "PHASE 1: Prepare context" as in_progress
... prepare (30s) ...
Mark "PHASE 1: Prepare context" as completed
Step 2: PHASE 2 (Parallel Execution)
Mark all 5 reviews as in_progress:
[→] Claude review
[→] Grok review
[→] Gemini review
[→] GPT-5 review
[→] DeepSeek review
Launch all 5 in parallel (4-Message Pattern)
As each completes:
T=60s: Claude completes
[✓] Claude review
User sees: "1/5 reviews complete"
T=90s: Gemini completes
[✓] Gemini review
User sees: "2/5 reviews complete"
T=120s: GPT-5 completes
[✓] GPT-5 review
User sees: "3/5 reviews complete"
T=150s: Grok completes
[✓] Grok review
User sees: "4/5 reviews complete"
T=180s: DeepSeek completes
[✓] DeepSeek review
User sees: "5/5 reviews complete!"
Step 3: PHASE 3
Mark "PHASE 3: Consolidate" as in_progress
... consolidate (30s) ...
Mark "PHASE 3: Consolidate" as completed
Step 4: PHASE 4
Mark "PHASE 4: Present results" as in_progress
... present (10s) ...
Mark "PHASE 4: Present results" as completed
Final State:
[✓] All 8 tasks completed
User sees: "Multi-model review complete in 3 minutes"
User Experience:
- Real-time progress as each model completes
- Clear visibility: "3/5 reviews complete"
- Reduces perceived wait time (user knows progress)
Troubleshooting
Problem: User thinks workflow is stuck
Cause: No TodoWrite updates for >1 minute
Solution: Update TodoWrite more frequently, or add sub-tasks
❌ Wrong:
[→] PHASE 3: Implementation (in_progress for 10 minutes)
✅ Correct:
[✓] PHASE 3: Implement core logic (2 min)
[✓] PHASE 3: Add error handling (3 min)
[→] PHASE 3: Write tests (in_progress, 2 min so far)
User sees progress every 2-3 minutes
Problem: Too many tasks (>20), overwhelming
Cause: Too granular task breakdown
Solution: Group micro-tasks into larger operations
❌ Wrong (25 tasks):
[ ] Read file 1
[ ] Read file 2
[ ] Write file 3
... (25 micro-tasks)
✅ Correct (8 tasks):
[ ] PHASE 1: Gather inputs (includes reading files)
[ ] PHASE 2: Process data
... (8 significant operations)
Problem: Multiple tasks "in_progress" (not parallel execution)
Cause: Forgot to mark previous task as completed
Solution: Always mark completed before starting next
❌ Wrong:
[→] PHASE 1: Ask user (in_progress)
[→] PHASE 2: Plan (in_progress) ← Both in_progress?
✅ Correct:
[✓] PHASE 1: Ask user (completed)
[→] PHASE 2: Plan (in_progress) ← Only one
Summary
TodoWrite orchestration provides real-time progress visibility through:
- Phase initialization (create task list before starting)
- Appropriate granularity (8-15 tasks, significant operations)
- Real-time updates (mark completed immediately)
- Exactly one in_progress (except parallel execution)
- Iteration tracking (separate task per iteration)
- Parallel task tracking (update as each completes)
Master these patterns and users will always know:
- What's happening now
- What's coming next
- How much progress has been made
- How much remains
This transforms "black box" workflows into transparent, trackable processes.
Extracted From:
/reviewcommand (10-task initialization, phase-based tracking)/implementcommand (8-phase workflow with sub-tasks)/validate-uicommand (iteration tracking, user feedback rounds)- All multi-phase orchestration workflows
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View allChoose optimal external AI models for code analysis, bug investigation, and architectural decisions. Use when consulting multiple LLMs via claudish, comparing model perspectives, or investigating complex Go/LSP/transpiler issues. Provides empirically validated model rankings (91/100 for MiniMax M2, 83/100 for Grok Code Fast) and proven consultation strategies based on real-world testing.
CRITICAL - Guide for using Claudish CLI ONLY through sub-agents to run Claude Code with OpenRouter models (Grok, GPT-5, Gemini, MiniMax). NEVER run Claudish directly in main context unless user explicitly requests it. Use when user mentions external AI models, Claudish, OpenRouter, or alternative models. Includes mandatory sub-agent delegation patterns, agent selection guide, file-based instructions, and strict rules to prevent context window pollution.
MANDATORY tracking protocol for multi-model validation. Creates structured tracking tables BEFORE launching models, tracks progress during execution, and ensures complete results presentation. Use when running 2+ external AI models in parallel. Trigger keywords - "multi-model", "parallel review", "external models", "consensus", "model tracking".
XML tag structure patterns for Claude Code agents and commands. Use when designing or implementing agents to ensure proper XML structure following Anthropic best practices.