Spawn Planning Agents

Spawn Planning Agents

Use specialized agents to gather context needed for creating detailed implementation plans.

Planning Research Needs

When planning implementations, you need:

1. Existing code patterns - How is similar functionality implemented?
2. Integration points - What files will need to change?
3. Test patterns - How should tests be written?
4. Documentation - What prior decisions or research exists?

Agent Selection for Planning

Find what exists:

• codebase-locator - Find files related to the feature area
• thoughts-locator - Find existing plans, research, or tickets

Understand patterns:

• codebase-pattern-finder - Find similar features to model after
• codebase-analyzer - Understand existing architecture

Extract insights:

• thoughts-analyzer - Extract key decisions from prior research

Planning Workflow

1. Context gathering (parallel):

   • Locate existing code in the feature area
   • Find similar implementations to model after
   • Check for prior research or decisions

2. Pattern analysis (parallel, after context):

   • Analyze architecture of similar features
   • Understand integration points

3. Plan creation:

   • Use findings to inform phases
   • Reference specific files and patterns
   • Include concrete examples from codebase

Example

Planning task: "Add email notifications feature"

Step 1 - Context (parallel):

Task(subagent_type="codebase-locator", prompt="Find all notification-related code")
Task(subagent_type="codebase-pattern-finder", prompt="Find examples of background job handlers and email sending")
Task(subagent_type="thoughts-locator", prompt="Find any research about notification systems")

Step 2 - Analysis (after context):

Task(subagent_type="codebase-analyzer", prompt="Analyze how the existing SMS notification system works, including job queuing and template rendering")

Step 3 - Plan with specifics: Reference the patterns found and create phases that follow existing conventions.

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