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22a1b25977
Fixes found by running the discovery workflow against the AWS CardDemo mainframe sample (~50 KLOC of COBOL/CICS/JCL/BMS/VSAM): - modernize-assess: add scc -> cloc -> find/wc fallback chain with the COCOMO-II formula so Step 1 works when scc isn't installed; same for portfolio-mode cloc/lizard. Drop the reference to a specific agent-spawning tool name (just "in parallel"). Sharpen the structural- map subagent prompt: 5-12 domains, subgraph clustering, ~40-edge cap, repo-relative paths, dangling-reference check. - modernize-map: expand the parse-target list with the things a literal-minded reader would miss on a real mainframe codebase — CICS CSD DEFINE TRANSACTION/FILE for entry points and online file I/O, EXEC CICS file ops, SELECT...ASSIGN TO joined with JCL DD, EXEC SQL table refs (not JCL DD), SEND/RECEIVE MAP, dynamic data-name XCTL resolution, COBOL fixed-format column slicing. Without these the dead-code list is wrong (most CICS programs look unreachable). Also write a machine-readable topology.json alongside the summary. - modernize-extract-rules: add a Priority (P0/P1/P2) field with a heuristic, and an optional Suspected-defect field. modernize-brief reads P0 rules to build the behavior contract, but the Rule Card had no priority slot — the chain was broken. - modernize-brief: read the new P0 tags; flag low-confidence P0 rules as SME blockers. - modernize-reimagine: drop "for the demo" wording. - security-auditor agent: add mainframe/COBOL coverage items (RACF, JCL/PROC creds, BMS field validation, DB2 dynamic SQL, copybook PII) and mark web-only items as such so it adapts to the target stack. - README: add Optional Tooling section and a symlink example for the expected layout.
84 lines
3.7 KiB
Markdown
84 lines
3.7 KiB
Markdown
---
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description: Multi-agent greenfield rebuild — extract specs from legacy, design AI-native, scaffold & validate with HITL
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argument-hint: <system-dir> <target-vision>
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---
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**Reimagine** `legacy/$1` as: $2
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This is not a port — it's a rebuild from extracted intent. The legacy system
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becomes the *specification source*, not the structural template. This command
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orchestrates a multi-agent team with explicit human checkpoints.
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## Phase A — Specification mining (parallel agents)
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Spawn concurrently and show the user that all three are running:
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1. **business-rules-extractor** — "Extract every business rule from legacy/$1
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into Given/When/Then form. Output to a structured list I can parse."
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2. **legacy-analyst** — "Catalog every external interface of legacy/$1:
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inbound (screens, APIs, batch triggers, queues) and outbound (reports,
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files, downstream calls, DB writes). For each: name, direction, payload
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shape, frequency/SLA if discernible."
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3. **legacy-analyst** — "Identify the core domain entities in legacy/$1 and
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their relationships. Return as an entity list + Mermaid erDiagram."
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Collect results. Write `analysis/$1/AI_NATIVE_SPEC.md` containing:
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- **Capabilities** (what the system must do — derived from rules + interfaces)
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- **Domain Model** (entities + erDiagram)
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- **Interface Contracts** (each external interface as an OpenAPI fragment or
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AsyncAPI fragment)
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- **Non-functional requirements** inferred from legacy (batch windows, volumes)
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- **Behavior Contract** (the Given/When/Then rules — these are the acceptance tests)
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## Phase B — HITL checkpoint #1
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Present the spec summary. Ask the user **one focused question**: "Which of
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these capabilities are P0 for the reimagined system, and are there any we
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should deliberately drop?" Wait for the answer. Record it in the spec.
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## Phase C — Architecture (single agent, then critique)
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Design the target architecture for "$2":
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- Mermaid C4 Container diagram
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- Service boundaries with rationale (which rules/entities live where)
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- Technology choices with one-line justification each
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- Data migration approach from legacy stores
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Then spawn **architecture-critic**: "Review this proposed architecture for
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$2 against the spec in analysis/$1/AI_NATIVE_SPEC.md. Identify over-engineering,
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missed requirements, scaling risks, and simpler alternatives." Incorporate
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the critique. Write the result to `analysis/$1/REIMAGINED_ARCHITECTURE.md`.
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## Phase D — HITL checkpoint #2
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Enter plan mode. Present the architecture. Wait for approval.
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## Phase E — Parallel scaffolding
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For each service in the approved architecture (cap at 3 to keep the run
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tractable; tell the user which you deferred), spawn a **general-purpose agent
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in parallel**:
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"Scaffold the <service-name> service per analysis/$1/REIMAGINED_ARCHITECTURE.md
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and AI_NATIVE_SPEC.md. Create: project skeleton, domain model, API stubs
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matching the interface contracts, and **executable acceptance tests** for every
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behavior-contract rule assigned to this service (mark unimplemented ones as
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expected-failure/skip with the rule ID). Write to modernized/$1-reimagined/<service-name>/."
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Show the agents' progress. When all complete, run the acceptance test suites
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and report: total tests, passing (scaffolded behavior), pending (rule IDs
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awaiting implementation).
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## Phase F — Knowledge graph handoff
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Write `modernized/$1-reimagined/CLAUDE.md` — the persistent context file for
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the new system, containing: architecture summary, service responsibilities,
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where the spec lives, how to run tests, and the legacy→modern traceability
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map. This file IS the knowledge graph that future agents and engineers will
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load.
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Report: services scaffolded, acceptance tests defined, % behaviors with a
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home, location of all artifacts.
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