ajbcoding/claude-skill-eval/moai-alfred-clone-pattern

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Enterprise Master-Clone pattern implementation guide for complex multi-step tasks with full project context, autonomous delegation, parallel processing, and intelligent task distribution; activates for large-scale migrations, complex refactoring, parallel exploration, architecture restructuring, and multi-file transformations

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npx vskill@latest install ajbcoding/claude-skill-eval/moai-alfred-clone-pattern

SKILL.md

Enterprise Master-Clone Pattern Skill v4.0.0

Skill Metadata

FieldValue
Skill Namemoai-alfred-clone-pattern
Version4.0.0 Enterprise (2025-11-12)
Allowed toolsRead, Bash, Task
Auto-loadOn demand for complex multi-step tasks
TierAlfred (Orchestration)
Lines of Content900+ with 12+ enterprise examples
Progressive Disclosure3-level (quick-start, patterns, advanced)

What It Does

Provides comprehensive guidance for Alfred's Master-Clone pattern - a delegation mechanism where Alfred creates autonomous clones (Task-delegated agents) to handle complex multi-step tasks that don't require domain-specific expertise but benefit from:

  • Full project context and codebase understanding
  • Parallel processing capabilities
  • Independent decision-making
  • Comprehensive state tracking

When to Use (Decision Framework)

Use Clone Pattern when:

  • Task requires 5+ sequential steps OR affects 100+ files
  • No domain-specific expertise needed (not UI, Backend, DB, Security, ML)
  • Task is complex with high uncertainty
  • Parallel processing would be beneficial
  • Full project context is required for optimal decisions
  • Task can run autonomously without continuous user input

Examples:

  • Large-scale migrations (v0.14.0 → v0.15.2 affecting 200 files)
  • Refactoring across many files (100+ imports, API changes)
  • Parallel exploration/evaluation tasks
  • Complex architecture restructuring
  • Bulk file transformations with context-aware logic
  • Schema migrations affecting multiple services
  • Dependency upgrade cascades

DON'T use Clone Pattern when:

  • Domain expertise needed (use specialist agents instead)
  • Task < 5 steps (direct execution is faster)
  • Quick yes/no decision (use AskUserQuestion)
  • Single file modification (use tdd-implementer)

Key Concepts

Master-Clone Architecture
Master Agent (Alfred)
↓ Creates with Task()
Clone Agent #1 Clone Agent #2 Clone Agent #3
(Parallel execution with shared context)
↓ ↓ ↓
[Exploration] [Analysis] [Implementation]
↓ ↓ ↓
Results aggregation & synthesis by Master
↓
User presentation + next steps

Master Responsibilities:

  • Analyze task scope and complexity
  • Decompose into independent parallel work
  • Create clones with appropriate context
  • Aggregate and synthesize results
  • Present findings to user

Clone Responsibilities:

  • Execute assigned sub-task autonomously
  • Use full project context for intelligent decisions
  • Track state and progress
  • Report findings with evidence
  • Handle errors gracefully

3-Level Architecture

Level 1: Simple Parallel Task

Scenario: Explore multiple implementation approaches in parallel

typescript
// Master agent: Create parallel clones for exploration
const clones = [
Task({
description: "Explore PostgreSQL implementation for user persistence",
prompt: "Analyze PostgreSQL libraries, schema design, migration strategy. Provide pros/cons and code examples."
}),
Task({
description: "Explore MongoDB implementation for user persistence",
prompt: "Analyze MongoDB libraries, document schema, migration strategy. Provide pros/cons and code examples."
}),
Task({
description: "Explore Supabase implementation for user persistence",
prompt: "Analyze Supabase SDK, schema design, migration strategy. Provide pros/cons and code examples."
})
];
// Wait for all parallel clones to complete
const [postgresAnalysis, mongoAnalysis, supabaseAnalysis] = await Promise.all(clones);
// Master synthesizes results
const comparison = {
options: [postgresAnalysis, mongoAnalysis, supabaseAnalysis],
recommendation: selectBestOption(clones),
tradeoffs: analyzeTradeoffs(clones)
};
Level 2: Sequential Dependent Tasks

Scenario: Complex migration where later steps depend on earlier analysis

typescript
// Step 1: Analyze current state
const analysisResult = await Task({
description: "Analyze v0.14.0 codebase structure",
prompt: "Scan project for all imports of 'old-api'. Document usage patterns, edge cases, and dependencies. Provide summary with file-by-file breakdown."
});
// Step 2: Plan migration strategy (depends on analysis)
const planResult = await Task({
description: "Plan migration strategy from v0.14.0 to v0.15.2",
prompt: `Using this analysis: ${analysisResult}\n\nCreate a step-by-step migration plan with:\n- Phased approach (phase 1, 2, 3)\n- Risk mitigation\n- Testing strategy\n- Rollback procedure`
});
// Step 3: Execute migration (depends on plan)
const migrationResult = await Task({
description: "Execute v0.14.0 → v0.15.2 migration",
prompt: `Using this plan: ${planResult}\n\nExecute the migration:\n- Update imports\n- Modify APIs\n- Update tests\n- Verify compatibility`
});
// Step 4: Validate results (depends on migration)
const validationResult = await Task({
description: "Validate migration completeness",
prompt: `Verify migration:\n- All imports updated\n- No breaking changes\n- Tests passing\n- Performance metrics maintained`
});
// Master reports final state
return {
analysis: analysisResult,
plan: planResult,
migration: migrationResult,
validation: validationResult,
status: validationResult.passed ? "SUCCESS" : "NEEDS_REVIEW"
};
Level 3: Hybrid Parallel + Sequential (Advanced)

Scenario: Large refactoring with parallel analysis, synchronized implementation

typescript
// Phase 1: Parallel analysis clones
const [apiAnalysis, dbAnalysis, authAnalysis] = await Promise.all([
Task({ description: "Analyze API layer usage...", prompt: "..." }),
Task({ description: "Analyze DB layer usage...", prompt: "..." }),
Task({ description: "Analyze Auth layer usage...", prompt: "..." })
]);
// Phase 2: Synchronized implementation (waits for all analyses)
const [apiRefactor, dbRefactor, authRefactor] = await Promise.all([
Task({
description: "Refactor API layer",
prompt: `Based on analysis:\n${apiAnalysis}\n\nRefactor API with:\n- New patterns\n- Tests\n- Documentation`
}),
Task({
description: "Refactor DB layer",
prompt: `Based on analysis:\n${dbAnalysis}\n\nRefactor DB with:\n- Schema updates\n- Migration scripts\n- Tests`
}),
Task({
description: "Refactor Auth layer",
prompt: `Based on analysis:\n${authAnalysis}\n\nRefactor Auth with:\n- New strategy\n- Migration\n- Tests`
})
]);
// Phase 3: Integration validation
const integrationResult = await Task({
description: "Validate refactored layer integration",
prompt: `Verify all refactored layers work together:\n- API uses new DB patterns\n- Auth integrates with API\n- No breaking changes\n- All tests passing`
});
return {
phase1: { apiAnalysis, dbAnalysis, authAnalysis },
phase2: { apiRefactor, dbRefactor, authRefactor },
phase3: integrationResult,
status: "COMPLETE"
};

Best Practices

DO
  • Define clear sub-tasks: Each clone should have a specific, measurable goal
  • Provide full context: Include project structure, existing patterns, constraints
  • Use sequential when needed: Depend on earlier results when necessary
  • Validate results: Always verify clone outputs before proceeding
  • Document findings: Track what each clone discovered
  • Handle failures gracefully: Plan for individual clone failures
  • Aggregate intelligently: Synthesize parallel results into coherent analysis
DON'T
  • Over-parallelize: Creating 20 clones is overkill (use 2-5)
  • Under-specify tasks: Vague descriptions lead to mediocre results
  • Ignore dependencies: Force sequential when tasks actually depend
  • Skip validation: Trust but verify clone outputs
  • Lose context: Always include relevant project information
  • Create circular dependencies: Avoid Task A waiting on Task B waiting on Task A

Implementation Patterns

Pattern 1: Exploration with Synthesis
typescript
// Create 3 clones exploring different approaches
const explorations = await Promise.all(approaches.map(approach =>
Task({
description: `Explore ${approach.name} approach`,
prompt: `Research ${approach.name}...\nProvide: pros, cons, code example, learning curve`
})
));
// Master synthesizes into comparison table
return {
comparison: createComparisonTable(explorations),
recommendation: selectBestApproach(explorations),
decisionRationale: explainDecision(explorations)
};
Pattern 2: Phased Migration
typescript
// Phase 1: Analyze
const analysis = await analyzeCurrentState();
// Phase 2: Plan (depends on analysis)
const plan = await planMigration(analysis);
// Phase 3: Implement (depends on plan)
const implementation = await implementMigration(plan);
// Phase 4: Validate (depends on implementation)
const validation = await validateMigration(implementation);
return { analysis, plan, implementation, validation };
Pattern 3: Distributed Refactoring
typescript
// Split files into groups, refactor each group in parallel
const fileGroups = splitFilesIntoGroups(files, 5);
const refactorResults = await Promise.all(
fileGroups.map(group =>
Task({
description: `Refactor files: ${group.join(", ")}`,
prompt: `Refactor these files using new patterns:\n${group.join("\n")}`
})
)
);
// Master validates all refactored files work together
return validateIntegration(refactorResults);

When NOT to Use (Anti-Patterns)

ScenarioWhyUse Instead
Single file changeToo much overheadDirect tdd-implementer
2-3 quick stepsSequential simplerDirect execution
Domain expertise requiredNeeds specialistSpecialist agent (security, DB, etc.)
Real-time interactionClones run independentlyInteractive agent
Simple queryOverkill complexityDirect lookup

Related Skills

  • moai-alfred-agent-guide (Agent architecture & delegation)
  • moai-alfred-task-decomposition (Breaking down complex tasks)
  • moai-essentials-refactor (Refactoring patterns & examples)

For detailed API specifications: reference.md For real-world examples: examples.md Last Updated: 2025-11-12 Status: Production Ready (Enterprise v4.0.0)

Security

  • Security scanPassed, 95 of 100Pattern checks on the skill's files.
  • Model reviewPassed

Quality evaluation

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Source

Popularity

Repository stars
4
7-day trend score
8

Stars and forks are for the whole GitHub repository, not this skill alone. Refreshed 23 Mar 2026, 7 months ago.

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