Nw Hotspot logo

Nw Hotspot

Organization
nWave-ai
nw-hotspot

Git change frequency hotspot analysis — find the most-changed files in your codebase

Overview

PublishernWave-ai
RepositorynWave
Skill namenw-hotspot
Stars
616
Forks
65
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by nWave-ai on GitHub. Read the source before you install it.

Installation

Install the Nw Hotspot AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/nWave-ai/nWave/tree/main/nWave/skills/nw-hotspot
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/nWave-ai/nWave.git /tmp/nWave
mkdir -p .claude/skills
cp -r /tmp/nWave/nWave/skills/nw-hotspot .claude/skills/nw-hotspot
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Nw Hotspot in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Nw Hotspot on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Nw Hotspot is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

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.

Frequently asked questions

What does the Nw Hotspot AI skill do?

Git change frequency hotspot analysis — find the most-changed files in your codebase

Why use Nw Hotspot on TypingMind?

Because you install it once and use it with any model. Nw Hotspot is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Nw Hotspot in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/nWave-ai/nWave/tree/main/nWave/skills/nw-hotspot. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Nw Hotspot?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Nw Hotspot?

As many as you like. As long as a model supports skills, you can use Nw Hotspot with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Nw Hotspot AI skill free?

Yes. It is published on GitHub by nWave-ai under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇