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2026-01-104

name	task-delegation
description	Project-agnostic skill for delegating execution work to subagents with skill activation, parallel execution, and quality verification.

Task Delegation Skill

Delegation Pattern

Plan → Create Task → Design Approach → Delegate → Review → Commit

Main Thread (You): Planning, architecture, coordination, review, user communication Subagents: Execution of well-defined work items with clear outputs

When to Delegate

✅ Always delegate:

Execution work taking >5 minutes of focused effort
Writing, research, analysis with defined scope
Work that can run in parallel with other tasks
Repetitive mechanical tasks (formatting, compilation, migration)
Well-defined scope with clear output format

✅ Benefits:

Parallel execution across independent tasks
Better planning with full project context
Focused execution produces higher quality
Cost optimization through model assignment

When NOT to Delegate

❌ Never delegate:

Task creation or search (use MCP tools directly in main thread)
Planning and architectural decisions (requires full context)
Editorial judgment (requires project continuity)
Answering user questions (requires conversation flow)
Dependency modeling (requires cross-task analysis)
Work taking <5 minutes (delegation overhead exceeds execution time)

Model Assignment Strategy

Choose model based on task complexity and cost optimization:

Task Type	Model	Rationale
Simple mechanical work	Haiku	Cost-efficient; Skills compensate for smaller model
Research compilation	Haiku	Search and compile work; Skills enforce quality
Structured writing	Sonnet	Balance capability/cost; structured output
Technical analysis	Sonnet	Synthesis required beyond Haiku capability
Deep critique	Opus	Maximum analytical insight needed
Complex synthesis	Opus	Scholarly rigor, philosophical depth, 10K+ word expansion

Cost Optimization Principle: Use smallest model capable of task with Skills active. Skills elevate Haiku/Sonnet to achieve quality standards previously requiring larger models.

How to Assign:

Check task's assignee field in Backlog (if project uses task assignment)
Specify model explicitly when delegating: model='haiku' or model='opus'
Default to Sonnet for general-purpose work if uncertain

Task Description for Skill Activation

Skills activate automatically when task description contains trigger keywords.

Pattern: [Action] + [Skill Trigger] + [Context]

Examples:

# Activates essay-research-compilation skill
"Compile comprehensive research for Essay 11 (Step 1)"

# Activates essay-first-draft skill
"Write first draft for Essay 11 based on research.md (Step 2)"

# Activates essay-critique skill
"Create comprehensive critique for Essay 11 draft (Step 3)"

Trigger Keywords by Skill Type:

Research: "research compilation", "Step 1", "gather sources", "compile research"
Drafting: "first draft", "Step 2", "write draft"
Critique: "comprehensive critique", "Step 3", "analyze draft"
Final drafts: "final draft", "Step 4", "expand to 10,000 words"

Best Practices:

Include step number if workflow uses numbered steps
Reference input files explicitly ("based on research.md")
State output format ("produce draft-1.md")
Keep description concise but keyword-rich for matching

Verifying Skill Activation

After delegating, check subagent's initial response for Skill confirmation.

Positive Confirmation:

"Using essay-research-compilation Skill to guide research compilation..."
"Activating essay-first-draft Skill for structured writing..."

If Skill Did NOT Activate:

Check task description for missing trigger keywords
Redelegate with clearer keywords: "research compilation (Step 1)" not just "gather data"
Confirm Skill exists in .claude/skills/ directory
Verify Skill's trigger patterns in SKILL.md frontmatter

Why Activation Matters: Skills provide comprehensive templates, examples, and verification checklists. Without activation, subagent lacks guidance that prevents common errors.

Delegation Workflow

1. Plan in Main Thread

Understand full scope and dependencies
Break work into independent subtasks if possible
Identify which subtasks can run in parallel
Design approach and output format

2. Create Tasks (if using Backlog)

# Create parent task
task_create(title, description, acceptanceCriteria, assignee=['model-name'])

# Create subtasks with dependencies
task_create(title, description, parentTaskId='parent-id', assignee=['haiku'])

3. Delegate to Subagent

# Single delegation
Task tool with:
  - Clear description (triggers Skills)
  - Model specification (haiku/sonnet/opus)
  - Reference to input files
  - Expected output format

# Parallel delegation (independent tasks)
Multiple Task tool calls in single message:
  - Task 1: "Research Essay 3 (Step 1)" → haiku
  - Task 2: "Research Essay 5 (Step 1)" → haiku
  - Task 3: "Research Essay 10 (Step 1)" → haiku

4. Review Output

Check against task acceptance criteria
Verify Skill guidelines followed (see Skill's verification checklist)
Confirm output format matches expectations
Test for scope creep (output should match defined scope, nothing more)

5. Commit and Document

git commit -m "[task-id] Brief description

Detailed explanation of what was completed."

Update task with commit reference:

task_edit(id='task-id', notesAppend=['Completed in commit abc123'])

Parallel Execution

Pattern: Launch multiple subagents for independent tasks in single message.

When to Use:

Tasks have no dependencies between them
Different essays at same workflow step
Different sections of large document
Independent research compilations

Example:

# Single message with 3 parallel Task tool calls:
Task 1: "Research Essay 3 Data Readiness (Step 1)" model=haiku
Task 2: "Research Essay 5 Technical Debt (Step 1)" model=haiku
Task 3: "Research Essay 10 Infrastructure (Step 1)" model=haiku

Benefits:

Maximize throughput (3 tasks complete in parallel vs sequential)
Efficient use of session time
No coordination overhead (tasks are independent)

Dependency Modeling: If Task B depends on Task A output, run sequentially:

Delegate Task A, wait for completion
Review Task A output
Delegate Task B with reference to Task A output

Reviewing Subagent Output

Verification Checklist:

Completeness:
- All acceptance criteria met?
- Output file exists at expected path?
- Required sections present?
Skill Adherence:
- Check against Skill's verification checklist (in SKILL.md)
- Example: essay-research-compilation requires 100% citation completeness
- Example: essay-first-draft requires minimum 5 human experience paragraphs
Format:
- Matches expected structure?
- File naming correct?
- No unexpected additions?
Scope:
- Output matches defined scope (no scope creep)?
- Subagent didn't make editorial decisions requiring main thread judgment?

If Quality Insufficient:

Provide specific feedback referencing Skill section
Example: "Section 2 needs causal analysis per essay-first-draft guidelines"
Redelegate with clarification, not vague "improve this"

Handling Subagent Failures

Common Issues and Fixes:

Issue	Root Cause	Fix
Skill didn't activate	Missing trigger keywords	Redelegate with "Step X" or skill name in description
Output missing required sections	Unclear acceptance criteria	Add specific checklist to task description
Scope creep	Vague task description	Define exact input files and output format
Wrong model used	Model not specified	Explicitly set model parameter in Task tool
Quality below standard	Skill verification skipped	Review against Skill checklist, return specific sections

Escalation Pattern:

First attempt: Redelegate with clarification
Second attempt: Provide Skill excerpt as context
Third attempt: Break into smaller subtasks or execute in main thread

Success Criteria

Well-delegated task produces:

✅ Output matching acceptance criteria exactly
✅ Skill guidelines followed (verified via checklist)
✅ No scope creep (output ≤ defined scope)
✅ Correct format and location
✅ Can commit immediately without revision

Signs of poor delegation:

❌ Multiple revision rounds needed
❌ Subagent made editorial decisions
❌ Output contains work outside defined scope
❌ Missing required sections
❌ Skill didn't activate (preventable with better description)

Quick Reference

Delegation Decision Tree:

Is this execution work >5 min? → NO → Do in main thread
  ↓ YES
Is scope well-defined? → NO → Plan first, then delegate
  ↓ YES
Can it run in parallel? → YES → Launch multiple subagents
  ↓ NO
Does it depend on other work? → YES → Wait for dependency
  ↓ NO
Delegate with:
  - Clear description (trigger Skills)
  - Model assignment (haiku/sonnet/opus)
  - Input files referenced
  - Output format specified

Model Selection:

Mechanical/research → Haiku
Structured writing → Sonnet
Complex synthesis → Opus
When uncertain → Sonnet (balanced default)

Parallel Pattern:

Independent tasks → Single message, multiple Task calls
Dependent tasks → Sequential delegation

Review Pattern:

Check acceptance criteria
Verify Skill checklist
Confirm format
Test scope