ensemble-solving

安装量: 39
排名: #18186

安装

npx skills add https://github.com/mhattingpete/claude-skills-marketplace --skill ensemble-solving

Ensemble Problem Solving

Generate multiple solutions in parallel by spawning 3 subagents with different approaches, then evaluate and select the best result.

When to Use

Activation phrases:

"Give me options for..." "What's the best way to..." "Explore different approaches..." "I want to see alternatives..." "Compare approaches for..." "Which approach should I use..."

Good candidates:

Architecture decisions with trade-offs Code generation with multiple valid implementations API design with different philosophies Naming, branding, documentation style Refactoring strategies Algorithm selection

Skip ensemble for:

Simple lookups or syntax questions Single-cause bug fixes File operations, git commands Deterministic configuration changes Tasks with one obvious solution What It Does Analyzes the task to determine if ensemble approach is valuable Generates 3 distinct prompts using appropriate diversification strategy Spawns 3 parallel subagents to develop solutions independently Evaluates all solutions using weighted criteria Returns the best solution with explanation and alternatives summary Approach Step 1: Classify Task Type

Determine which category fits:

Code Generation: Functions, classes, APIs, algorithms Architecture/Design: System design, data models, patterns Creative: Writing, naming, documentation Step 2: Invoke Ensemble Orchestrator Task tool with: - subagent_type: 'ensemble-orchestrator' - description: 'Generate and evaluate 3 parallel solutions' - prompt: [User's original task with full context]

The orchestrator handles:

Prompt diversification Parallel execution Solution evaluation Winner selection Step 3: Present Result

The orchestrator returns:

The winning solution (in full) Evaluation scores for all 3 approaches Why the winner was selected When alternatives might be preferred Diversification Strategies

For Code (Constraint Variation):

Approach Focus Simplicity Minimal code, maximum readability Performance Efficient, optimized Extensibility Clean abstractions, easy to extend

For Architecture (Approach Variation):

Approach Focus Top-down Requirements → Interfaces → Implementation Bottom-up Primitives → Composition → Structure Lateral Analogies from other domains

For Creative (Persona Variation):

Approach Focus Expert Technical precision, authoritative Pragmatic Ship-focused, practical Innovative Creative, unconventional Evaluation Rubric Criterion Base Weight Description Correctness 30% Solves the problem correctly Completeness 20% Addresses all requirements Quality 20% How well-crafted Clarity 15% How understandable Elegance 15% How simple/beautiful

Weights adjust based on task type.

Example

User: "What's the best way to implement a rate limiter?"

Skill:

Classifies as Code Generation Invokes ensemble-orchestrator Three approaches generated: Simple: Token bucket with in-memory counter Performance: Sliding window with atomic operations Extensible: Strategy pattern with pluggable backends Evaluation selects extensible approach (score 8.4) Returns full implementation with explanation

Output:

Selected Solution

[Full rate limiter implementation with strategy pattern]

Why This Solution Won

The extensible approach scored highest (8.4) because it provides a clean abstraction that works for both simple use cases and complex distributed scenarios. The strategy pattern allows swapping Redis/Memcached backends without code changes.

Alternatives

  • Simple approach: Best if you just need basic in-memory limiting and will never scale beyond one process.

  • Performance approach: Best for high-throughput scenarios where every microsecond matters.

Success Criteria 3 genuinely different solutions generated Clear evaluation rationale provided Winner selected with confidence Alternatives summarized with use cases User understands trade-offs Token Cost

~4x overhead vs single attempt. Worth it for:

High-stakes architecture decisions Creative work where first attempt rarely optimal Learning scenarios where seeing alternatives is valuable Code that will be maintained long-term Integration feature-planning: Can ensemble architecture decisions code-auditor: Can ensemble analysis perspectives plan-implementer: Executes the winning approach

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