126 lines
3.7 KiB
Markdown
Executable File
126 lines
3.7 KiB
Markdown
Executable File
---
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description: Discuss multi-agent workflow strategy for a specific task
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argument-hint: [task-description]
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allowed-tools: Read, Task, TodoWrite
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---
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# Multi-Agent Workflow Discussion
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Prepare to discuss how you will use a multi-agent workflow to ${ARGUMENTS}.
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## Instructions
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1. **Analyze the Task**: ${ARGUMENTS}
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- Break down the complexity
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- Identify parallelizable components
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- Determine if multi-agent approach is optimal
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2. **Evaluate Approach**:
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- Should this use `/background` (single agent) or `/orchestrate` (multiple agents)?
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- How many agents would be optimal?
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- What are the dependencies between subtasks?
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3. **Design Strategy**:
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- Outline the orchestration plan
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- Define agent responsibilities
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- Specify communication format (JSON responses)
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- Identify quality gates
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4. **Provide Recommendations**:
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- Best command to use (`/background` vs `/orchestrate`)
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- Number of agents (if using orchestrate: 2-8)
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- Subtask breakdown
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- Estimated completion time
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- Resource requirements
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## Output Format
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Provide a structured discussion covering:
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1. **Task Analysis**: Understanding of "${ARGUMENTS}"
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2. **Complexity Assessment**: Simple/Moderate/High
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3. **Recommended Approach**: `/background` or `/orchestrate`
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4. **Agent Breakdown** (if orchestrate):
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- Agent 1: Responsibility
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- Agent 2: Responsibility
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- ...
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5. **Dependencies**: None / Sequential / Hybrid
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6. **Estimated Time**: X minutes
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7. **Next Steps**: Commands to run
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## Examples
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### Example 1: Simple Task
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```
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User: /aa_command "optimize the g_x_mg_statsclasscount table"
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Output:
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Task Analysis: Single gold table optimization - focused work
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Complexity: Moderate
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Recommended: /background
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Reasoning: Single file, sequential optimization steps
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Estimated Time: 15 minutes
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Next Step: /background "Optimize g_x_mg_statsclasscount.py for performance"
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```
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### Example 2: Complex Task
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```
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User: /aa_command "implement data quality framework across all layers"
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Output:
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Task Analysis: Cross-layer feature implementation
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Complexity: High
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Recommended: /orchestrate
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Agent Breakdown:
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- Agent 1: Design quality schema and base classes
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- Agent 2: Implement bronze layer validators
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- Agent 3: Implement silver layer validators
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- Agent 4: Implement gold layer validators
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- Agent 5: Create validation tests
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- Agent 6: Update documentation
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Dependencies: Agent 1 must complete before 2-4 (hybrid approach)
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Estimated Time: 45-60 minutes
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Next Step: Create task file and run /orchestrate data_quality_framework.md
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```
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### Example 3: Medium Complexity
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```
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User: /aa_command "fix all linting errors in the silver layer"
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Output:
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Task Analysis: Code quality fixes across multiple files
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Complexity: Moderate-High
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Recommended: /orchestrate (if >15 files) or /background (if <15 files)
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Agent Breakdown:
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- Agent 1: Fix linting in silver_cms files
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- Agent 2: Fix linting in silver_fvms files
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- Agent 3: Fix linting in silver_nicherms files
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Dependencies: None (fully parallel)
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Estimated Time: 20-30 minutes
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Next Step: /orchestrate "Fix linting errors: silver_cms, silver_fvms, silver_nicherms in parallel"
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```
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## Usage
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```bash
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# Discuss strategy for any task
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/aa_command "optimize all gold tables for performance"
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# Get recommendations for feature implementation
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/aa_command "add monitoring and alerting to the pipeline"
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# Plan refactoring work
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/aa_command "refactor all ETL classes to use new base class pattern"
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# Evaluate testing strategy
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/aa_command "write comprehensive tests for the medallion architecture"
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```
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## Notes
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- This command helps you plan before executing
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- Use this to determine optimal agent strategy
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- Creates a blueprint for `/background` or `/orchestrate` commands
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- Considers parallelism, dependencies, and complexity
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- Provides concrete next steps and command examples
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