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task-delegation

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

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All-The-Vibes/skills-catalog
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10 de enero de 2026 a las 18:10
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SKILL.md
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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:** ```bash # 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) ```bash # 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 ```bash # 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 ```bash git commit -m "[task-id] Brief description Detailed explanation of what was completed." ``` Update task with commit reference: ```bash 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:** ```bash # 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
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