Blueprint

Blueprint — Construction Plan Generator

Turn a one-line objective into a step-by-step plan any coding agent can execute cold.

Overview

Blueprint is for multi-session, multi-agent engineering projects where each step must be independently executable by a fresh agent that has never seen the conversation history. Install it once, invoke it with /blueprint <project> <objective>.

When to Use This Skill

• Use when the task requires multiple PRs or sessions
• Use when multiple agents or team members need to share execution
• Use when you want adversarial review of the plan before execution
• Use when parallel step detection and dependency graphs matter

How It Works

1. Research — Scans the codebase, reads project memory, runs pre-flight checks
2. Design — Breaks the objective into one-PR-sized steps, identifies parallelism, assigns model tiers
3. Draft — Generates the plan from a structured template with branch workflow rules, CI policy, and rollback strategies inline
4. Review — Delegates adversarial review to a strongest-model sub-agent (falls back to default model if unavailable)
5. Register — Saves the plan and updates project memory

Examples

Example 1: Database migration

/blueprint myapp "migrate database to PostgreSQL"

Example 2: Plugin extraction

/blueprint antbot "extract providers into plugins"

Best Practices

• ✅ Use for tasks requiring 3+ PRs or multiple sessions
• ✅ Let Blueprint auto-detect git/gh availability — it degrades gracefully
• ❌ Don't invoke for tasks completable in a single PR
• ❌ Don't invoke when the user says "just do it"

Key Differentiators

• Cold-start execution: Every step has a self-contained context brief
• Adversarial review gate: Strongest-model review before execution
• Zero runtime risk: Pure markdown — no hooks, no scripts, no executable code
• Plan mutation protocol: Steps can be split, inserted, skipped with audit trail

Installation

mkdir -p ~/.claude/skills
git clone https://github.com/antbotlab/blueprint.git ~/.claude/skills/blueprint

Additional Resources

• GitHub Repository
• Examples: small plan
• Examples: large plan

AGI Framework Integration

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

Memory-First Protocol

Retrieve prior agent configurations, team compositions, and orchestration patterns. Critical for multi-agent system consistency.

# Check for prior AI agent orchestration context before starting
python3 execution/memory_manager.py auto --query "agent patterns and orchestration strategies for Blueprint"

Storing Results

After completing work, store AI agent orchestration decisions for future sessions:

python3 execution/memory_manager.py store \
  --content "Agent pattern: hierarchical orchestration with Control Tower dispatcher, 3 specialist sub-agents" \
  --type decision --project <project> \
  --tags blueprint ai-agents

Multi-Agent Collaboration

This skill is inherently multi-agent. Use cross-agent context to coordinate task distribution and avoid duplicate work.

python3 execution/cross_agent_context.py store \
  --agent "<your-agent>" \
  --action "Agent architecture designed — Control Tower + specialist agents with shared Qdrant memory" \
  --project <project>

Control Tower Integration

Register agents and tasks with the Control Tower (execution/control_tower.py) for centralized orchestration across machines and LLM providers.

Blockchain Identity

Each agent has a cryptographic Ed25519 identity. All memory writes are signed — enabling trust verification in multi-agent systems.