task-delegation

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

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When & Why to Use This Skill

The Task Delegation skill transforms Claude into a powerful project orchestrator capable of managing complex workflows by delegating execution to specialized subagents. It optimizes productivity through parallel execution, automated skill activation via keyword triggers, and a strategic model assignment system (Haiku, Sonnet, Opus) that balances high-quality output with cost efficiency. By implementing a 'Plan-Delegate-Review' pattern, it ensures rigorous quality verification and architectural consistency across multi-step projects.

Use Cases

  • Parallel Research and Analysis: Launching multiple subagents simultaneously to gather data on different topics, significantly reducing the time required for comprehensive market or academic research.
  • Multi-Stage Content Production: Orchestrating a pipeline where different models handle specific steps—such as Haiku for research compilation, Sonnet for structured drafting, and Opus for deep analytical critique.
  • Large-Scale Technical Migrations: Breaking down repetitive mechanical tasks like code formatting, documentation updates, or file migrations into independent subtasks for parallel subagent execution.
  • Automated Quality Assurance: Using subagents to perform rigorous verification against acceptance criteria and skill-specific checklists before final work is committed to the main project.
  • Cost-Effective Task Scaling: Optimizing operational costs by automatically assigning simpler mechanical work to smaller models while reserving advanced reasoning models for complex synthesis and architectural decisions.
nametask-delegation
descriptionProject-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:

  1. Check task description for missing trigger keywords
  2. Redelegate with clearer keywords: "research compilation (Step 1)" not just "gather data"
  3. Confirm Skill exists in .claude/skills/ directory
  4. 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:

  1. Delegate Task A, wait for completion
  2. Review Task A output
  3. Delegate Task B with reference to Task A output

Reviewing Subagent Output

Verification Checklist:

  1. Completeness:

    • All acceptance criteria met?
    • Output file exists at expected path?
    • Required sections present?
  2. 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
  3. Format:

    • Matches expected structure?
    • File naming correct?
    • No unexpected additions?
  4. 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:

  1. First attempt: Redelegate with clarification
  2. Second attempt: Provide Skill excerpt as context
  3. 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