claude-plugins-official/plugins/code-modernization/commands/modernize-assess.md

description, argument-hint

description	argument-hint
Full discovery & portfolio analysis of a legacy system — inventory, complexity, debt, effort estimation	<system-dir> | --portfolio <parent-dir>

Mode select. If $ARGUMENTS starts with --portfolio, run Portfolio mode against the directory that follows. Otherwise run Single-system mode against legacy/$1.

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Portfolio mode (--portfolio <parent-dir>)

Sweep every immediate subdirectory of the parent dir and produce a heat-map a steering committee can use to sequence a multi-year program.

Step P1 — Per-system metrics

For each subdirectory <sys>:

cloc --quiet --csv <parent>/<sys>          # LOC by language
lizard -s cyclomatic_complexity <parent>/<sys> 2>/dev/null | tail -1

Capture: total SLOC, dominant language, file count, mean & max cyclomatic complexity (CCN). For dependency freshness, locate the manifest (package.json, pom.xml, *.csproj, requirements*.txt, copybook dir) and note its age / pinned-version count.

Step P2 — COCOMO-II effort

Compute person-months per system using COCOMO-II basic: PM = 2.94 × (KSLOC)^1.10 (nominal scale factors). Show the formula and inputs so the figure is defensible, not a guess.

Step P3 — Documentation coverage

For each system, count source files with vs without a header comment block, and list architecture docs present (README, docs/, ADRs). Report coverage % and the top undocumented subsystems.

Step P4 — Render the heat-map

Write analysis/portfolio.html (dark #1e1e1e bg, #d4d4d4 text, #cc785c accent, system-ui font, all CSS inline). One row per system; columns: System · Lang · KSLOC · Files · Mean CCN · Max CCN · Dep Freshness · Doc Coverage % · COCOMO PM · Risk. Color-grade the PM and Risk cells (green→amber→red). Below the table, a 2-3 sentence sequencing recommendation: which system first and why.

Then stop. Tell the user to open analysis/portfolio.html.

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Single-system mode

Perform a complete modernization assessment of legacy/$1.

This is the discovery phase — the goal is a fact-grounded executive brief that a VP of Engineering could take into a budget meeting. Work in this order:

Step 1 — Quantitative inventory

Run and show the output of:

scc legacy/$1

Then run scc --by-file -s complexity legacy/$1 | head -25 to identify the highest-complexity files. Capture the COCOMO effort/cost estimate scc provides.

Step 2 — Technology fingerprint

Identify, with file evidence:

• Languages, frameworks, and runtime versions in use
• Build system and dependency manifest locations
• Data stores (schemas, copybooks, DDL, ORM configs)
• Integration points (queues, APIs, batch interfaces, screen maps)
• Test presence and approximate coverage signal

Step 3 — Parallel deep analysis

Spawn three subagents concurrently using the Task tool:

1. legacy-analyst — "Build a structural map of legacy/$1: what are the 5-10 major functional domains, which source files belong to each, and how do they depend on each other? Return a markdown table + a Mermaid graph TD of domain-level dependencies. Cite file paths."

2. legacy-analyst — "Identify technical debt in legacy/$1: dead code, deprecated APIs, copy-paste duplication, god objects/programs, missing error handling, hardcoded config. Return the top 10 findings ranked by remediation value, each with file:line evidence."

3. security-auditor — "Scan legacy/$1 for security vulnerabilities: injection, auth weaknesses, hardcoded secrets, vulnerable dependencies, missing input validation. Return findings in CWE-tagged table form with file:line evidence and severity."

Wait for all three. Synthesize their findings.

Step 4 — Production runtime overlay (observability)

If the system has batch jobs (e.g. JCL members under app/jcl/), call the observability MCP tool get_batch_runtimes for each business-relevant job name (interest, posting, statement, reporting). Use the returned p50/p95/p99 and 90-day series to:

• Tag each functional domain from Step 3 with its production wall-clock cost and p99 variance (p99/p50 ratio).
• Flag the highest-variance domain as the highest operational risk — this is telemetry-grounded, not a static-analysis opinion.

Include a small Batch Runtime table (Job · Domain · p50 · p95 · p99 · p99/p50) in the assessment.

Step 5 — Documentation gap analysis

Compare what the code does against what README/docs/comments say. List the top 5 undocumented behaviors or subsystems that a new engineer would need explained.

Step 6 — Write the assessment

Create analysis/$1/ASSESSMENT.md with these sections:

• Executive Summary (3-4 sentences: what it is, how big, how risky, headline recommendation)
• System Inventory (the scc table + tech fingerprint)
• Architecture-at-a-Glance (the domain table; reference the diagram)
• Production Runtime Profile (the batch-runtime table from Step 4, with the highest-variance domain called out)
• Technical Debt (top 10, ranked)
• Security Findings (CWE table)
• Documentation Gaps (top 5)
• Effort Estimation (COCOMO-derived person-months, ±range, key cost drivers)
• Recommended Modernization Pattern (one of: Rehost / Replatform / Refactor / Rearchitect / Rebuild / Replace — with one-paragraph rationale)

Also create analysis/$1/ARCHITECTURE.mmd containing the Mermaid domain dependency diagram from the legacy-analyst.

Step 7 — Present

Tell the user the assessment is ready and suggest: glow -p analysis/$1/ASSESSMENT.md