modernize-reimagine.md 3.7 KB
description: Multi-agent greenfield rebuild — extract specs from legacy, design AI-native, scaffold & validate with HITL
argument-hint:
Reimagine legacy/$1 as: $2
This is not a port — it's a rebuild from extracted intent. The legacy system becomes the specification source, not the structural template. This command orchestrates a multi-agent team with explicit human checkpoints.
Phase A — Specification mining (parallel agents)
Spawn concurrently and show the user that all three are running:
business-rules-extractor — "Extract every business rule from legacy/$1 into Given/When/Then form. Output to a structured list I can parse."
legacy-analyst — "Catalog every external interface of legacy/$1: inbound (screens, APIs, batch triggers, queues) and outbound (reports, files, downstream calls, DB writes). For each: name, direction, payload shape, frequency/SLA if discernible."
legacy-analyst — "Identify the core domain entities in legacy/$1 and their relationships. Return as an entity list + Mermaid erDiagram."
Collect results. Write analysis/$1/AI_NATIVE_SPEC.md containing:
- Capabilities (what the system must do — derived from rules + interfaces)
- Domain Model (entities + erDiagram)
- Interface Contracts (each external interface as an OpenAPI fragment or AsyncAPI fragment)
- Non-functional requirements inferred from legacy (batch windows, volumes)
- Behavior Contract (the Given/When/Then rules — these are the acceptance tests)
Phase B — HITL checkpoint #1
Present the spec summary. Ask the user one focused question: "Which of these capabilities are P0 for the reimagined system, and are there any we should deliberately drop?" Wait for the answer. Record it in the spec.
Phase C — Architecture (single agent, then critique)
Design the target architecture for "$2":
- Mermaid C4 Container diagram
- Service boundaries with rationale (which rules/entities live where)
- Technology choices with one-line justification each
- Data migration approach from legacy stores
Then spawn architecture-critic: "Review this proposed architecture for
$2 against the spec in analysis/$1/AI_NATIVE_SPEC.md. Identify over-engineering,
missed requirements, scaling risks, and simpler alternatives." Incorporate
the critique. Write the result to analysis/$1/REIMAGINED_ARCHITECTURE.md.
Phase D — HITL checkpoint #2
Enter plan mode. Present the architecture. Wait for approval.
Phase E — Parallel scaffolding
For each service in the approved architecture (cap at 3 for the demo), spawn a general-purpose agent in parallel:
"Scaffold the service per analysis/$1/REIMAGINED_ARCHITECTURE.md and AI_NATIVE_SPEC.md. Create: project skeleton, domain model, API stubs matching the interface contracts, and executable acceptance tests for every behavior-contract rule assigned to this service (mark unimplemented ones as expected-failure/skip with the rule ID). Write to modernized/$1-reimagined//."
Show the agents' progress. When all complete, run the acceptance test suites and report: total tests, passing (scaffolded behavior), pending (rule IDs awaiting implementation).
Phase F — Knowledge graph handoff
Write modernized/$1-reimagined/CLAUDE.md — the persistent context file for
the new system, containing: architecture summary, service responsibilities,
where the spec lives, how to run tests, and the legacy→modern traceability
map. This file IS the knowledge graph that future agents and engineers will
load.
Report: services scaffolded, acceptance tests defined, % behaviors with a home, location of all artifacts.