NW-HOTSPOT: Code Crime Scene Hotspot Lens

Wave: CROSS_WAVE Execution: Inline (no agent, Claude executes git commands directly) Inspiration: Adam Tornhill's "Your Code as a Crime Scene"

Overview

Analyze git change frequency to identify the most-changed files in a codebase. Pure git churn, no complexity metrics. Use as a pre-filter to scope analysis or a post-filter to prioritize existing findings.

How It Works

Run git log --name-only over the configured time period, count commits per file, rank by frequency.

Modes

1. Analyze (default)

Show the most-changed files in the repo. Output is inline only, no files persisted.

/nw-hotspot
/nw-hotspot --top=20
/nw-hotspot --since=12m

Steps:

1. Run: git log --since={since} --format=format: --name-only | sort | uniq -c | sort -rn
2. Exclude deleted files (verify each file still exists with test -f)
3. For each file, get last changed date: git log -1 --format="%ar" -- {file}
4. Display ranked table (top N):

 Rank │ Commits │ Last Changed │ File
──────┼─────────┼──────────────┼─────────────────────────
    1 │      87 │ 2 days ago   │ src/services/payment.ts
    2 │      64 │ 1 week ago   │ src/api/controllers/user.ts
    3 │      51 │ 3 days ago   │ src/models/order.ts

5. Show summary: total files changed in period, time period, top N shown

Defaults: --top: 15, --since: 6 months

2. Rank (post-filter)

Overlay churn data on an existing analysis report to prioritize findings.

/nw-hotspot --rank code-smell-detector-report.md

Steps:

1. Run the same git churn analysis
2. Read the specified report file
3. Extract file paths mentioned in the report
4. Annotate each file with its commit count
5. Re-sort findings by churn (highest first). Findings without extractable file paths go at the bottom.
6. Show noise reduction: "X of Y findings are in low-churn files (< 20 commits)"

3. Detail (deep-dive)