Concise Planning

Concise Planning

Goal

Turn a user request into a single, actionable plan with atomic steps.

Workflow

1. Scan Context

• Read README.md, docs, and relevant code files.
• Identify constraints (language, frameworks, tests).

2. Minimal Interaction

• Ask at most 1–2 questions and only if truly blocking.
• Make reasonable assumptions for non-blocking unknowns.

3. Generate Plan

Use the following structure:

• Approach: 1-3 sentences on what and why.
• Scope: Bullet points for "In" and "Out".
• Action Items: A list of 6-10 atomic, ordered tasks (Verb-first).
• Validation: At least one item for testing.

Plan Template

# Plan

<High-level approach>

## Scope

- In:
- Out:

## Action Items

[ ] <Step 1: Discovery>
[ ] <Step 2: Implementation>
[ ] <Step 3: Implementation>
[ ] <Step 4: Validation/​Testing>
[ ] <Step 5: Rollout/​Commit>

## Open Questions

- <Question 1 (max 3)>

Checklist Guidelines

• Atomic: Each step should be a single logical unit of work.
• Verb-first: "Add...", "Refactor...", "Verify...".
• Concrete: Name specific files or modules when possible.

When to Use

This skill is applicable to execute the workflow or actions described in the overview.

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AGI Framework Integration

Adapted for @techwavedev/​agi-agent-kit Original source: antigravity-awesome-skills

Memory-First Protocol

Retrieve prior Architecture Decision Records (ADRs), trade-off analyses, and system design rationale. Critical for maintaining consistency across long-running projects.

# Check for prior architecture/​design context before starting
python3 execution/​memory_manager.py auto --query "architecture decisions and trade-off analysis for Concise Planning"

Storing Results

After completing work, store architecture/​design decisions for future sessions:

python3 execution/​memory_manager.py store \
  --content "Architecture: event-driven microservices with CQRS, Pulsar for messaging, Qdrant for semantic search" \
  --type decision --project <project> \
  --tags concise-planning architecture

Multi-Agent Collaboration

Broadcast architecture decisions to ALL agents so implementation stays aligned with the chosen patterns.

python3 execution/​cross_agent_context.py store \
  --agent "<your-agent>" \
  --action "Completed architecture review — ADR documented, trade-offs analyzed, team aligned" \
  --project <project>

Control Tower Coordination

Register architecture tasks in the Control Tower so all agents across machines know the current system design and constraints.

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