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Nw hotspot

Skill nWave-ai/nWave/nWave/skills/nw-hotspot

Git change frequency hotspot analysis — find the most-changed files in your codebaseFrom its SKILL.md

Install
npx -y skills add nWave-ai/nWave --skill nw-hotspot

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SKILL.md

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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
  1. 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)

Deep-dive into a single file's change history.

/nw-hotspot --detail src/services/payment.ts

Steps:

  1. Monthly commit breakdown over the period
  2. Top contributors to the file
  3. Co-change coupling: top 5 files that frequently change alongside this one
  4. Last 10 commit messages for context

4. JSON export (pre-filter composition)

/nw-hotspot --top=10 --json

Output: [{"path": "src/services/payment.ts", "commits": 87, "last_changed": "2 days ago"}, ...]

Parameters

FlagDefaultDescription
--top15Number of files to show
--since6mTime period (e.g., 3m, 12m, 2024-01-01)
--jsonfalseOutput as JSON array
--rank-Path to existing report to re-rank by churn
--detail-Path to single file for deep-dive

Edge Cases

  • No commits in period: Display "No commits found since {date}" rather than an empty table
  • File renames: Counted as separate files (no --follow; keeps it simple and fast)
  • Empty repo / not a git repo: Display error and exit

Usage from Other Skills

Pre-filter (scope downstream analysis)

Run /nw-hotspot --top=10 --json first, then pass the file list to:

  • code-smell-detector: "Analyze only these files: {hotspot list}"
  • cognitive-load-analyzer: "Focus analysis on these files: {hotspot list}"
  • refactoring-expert: "Prioritize recommendations for these files"

Post-filter (rank existing findings)

Run /nw-hotspot --rank {report.md} after any analysis to prioritize by churn.

In nWave workflows

  • Before /nw-refactor — identify which files to refactor first
  • Before /nw-review — focus review effort on high-churn areas
  • Before /nw-root-why — check if the problematic area is a known hotspot

Next Wave

Usage Context: Inline utility, composable with any analysis skill Handoff To: Invoking context (no sequential handoff)

Examples

Example 1: Quick scan of a legacy codebase

/nw-hotspot

Example 2: Scope a code smell analysis to hotspots

/nw-hotspot --top=10 --json

Example 3: Prioritize an existing refactoring report

/nw-hotspot --rank code-refactoring-report.md

Example 4: Investigate a specific troubled file

/nw-hotspot --detail src/services/payment.ts

Expected Outputs

No persistent files. Output is displayed inline. JSON mode outputs a JSON array for composition with other tools.

What ships with it

Read from the repository

Just SKILL.md. No reference files, no scripts.

Keep looking

Skills are one crate of 325,949. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.