Btw logo

Btw

Organization
ww-w-ai
btw

Collect improvement suggestions during work. By-The-Way captures ideas, observations, and suggestions without interrupting the current workflow. Stores entries in .bkit/btw.json for later review and promotion. Use proactively when user says "btw", mentions a suggestion, improvement idea, or wants to note something for later. Triggers: btw, suggestion, improve, idea, feedback, note for later, by the way, 제안, 개선, 아이디어, 피드백, 참고로, 提案, 改善, アイデア, フィードバック, ちなみに, 建议, 改进, 想法, 反馈, 顺便说一下, sugerencia, mejora, idea, retroalimentación, amélioration, suggestion, idée, retour, Verbesserung, Vorschlag, Idee, Feedback, miglioramento, suggerimento, idea, feedback Do NOT use for: bug reports (use issues), task tracking (use PDCA)

Overview

Publisherww-w-ai
Repositorybkit-gemini
Skill namebtw
Stars
66
Forks
16
Bundled files
Instructions only
LicenseApache-2.0
Links
Skill sourceRepositoryHomepage
  • 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 ww-w-ai on GitHub. Read the source before you install it.

Installation

Install the Btw 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.
  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/ww-w-ai/bkit-gemini.git /tmp/bkit-gemini
mkdir -p .claude/skills
cp -r /tmp/bkit-gemini/skills/btw .claude/skills/btw
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Btw 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 Btw 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 Btw 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.

BTW (By-The-Way) Skill

Capture improvement suggestions on the fly without disrupting your workflow

Commands

CommandDescriptionExample
/btw "text"Record a new suggestion/btw "Consider adding input validation to user form"
/btw listShow all collected suggestions/btw list
/btw analyzeAnalyze and categorize suggestions/btw analyze
/btw promote [id]Promote suggestion to PDCA feature/btw promote 3

How It Works

Recording a Suggestion

  1. Read .bkit/btw.json (create if it does not exist)
  2. Append a new entry with:
    • id: Auto-incrementing integer
    • text: The suggestion text
    • timestamp: ISO 8601 date string
    • context: Current file or feature being worked on
    • status: pending (default)
    • category: Auto-detected (perf, ux, refactor, security, docs, other)
  3. Write the updated array back to .bkit/btw.json using write_file

Storage Format

json
{
  "entries": [
    {
      "id": 1,
      "text": "Consider caching API responses for /users endpoint",
      "timestamp": "2026-04-09T14:30:00Z",
      "context": "src/api/users.js",
      "status": "pending",
      "category": "perf"
    }
  ]
}

Listing Suggestions

  1. Read .bkit/btw.json
  2. Display entries in a table sorted by newest first
  3. Show status indicators: pending, promoted, dismissed

Analyzing Suggestions

  1. Read all entries from .bkit/btw.json
  2. Group by category
  3. Identify patterns and recurring themes
  4. Suggest which items to prioritize
  5. Estimate effort for each (low/medium/high)

Promoting to PDCA Feature

  1. Read the specified entry by ID
  2. Create a new PDCA plan document: docs/01-plan/features/{slug}.plan.md
  3. Pre-fill the plan with the suggestion details
  4. Update the entry status to promoted
  5. Inform user to continue with /pdca design {slug}

Categories

CategoryDetection Keywords
perfcache, speed, optimize, slow, performance, latency
uxuser, UI, UX, interface, experience, accessibility
refactorrefactor, cleanup, simplify, DRY, extract, reorganize
securitysecurity, auth, validation, sanitize, XSS, CSRF
docsdocument, README, comment, explain, JSDoc
otherEverything else

Integration with PDCA

BTW feeds into the Act phase:

  1. Collect suggestions during Do phase with /btw "..."
  2. Review collected items with /btw list
  3. Analyze patterns with /btw analyze
  4. Promote actionable items with /btw promote [id]
  5. Continue with standard PDCA flow for promoted items

Frequently asked questions

What does the Btw AI skill do?

Collect improvement suggestions during work. By-The-Way captures ideas, observations, and suggestions without interrupting the current workflow. Stores entries in .bkit/btw.json for later review and promotion. Use proactively when user says "btw", mentions a suggestion, improvement idea, or wants to note something for later. Triggers: btw, suggestion, improve, idea, feedback, note for later, by the way, 제안, 개선, 아이디어, 피드백, 참고로, 提案, 改善, アイデア, フィードバック, ちなみに, 建议, 改进, 想法, 反馈, 顺便说一下, sugerencia, mejora, idea, retroalimentación, amélioration, suggestion, idée, retour, Verbesserung, Vorschlag, Idee...

Why use Btw on TypingMind?

Because you install it once and use it with any model. Btw 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 Btw in TypingMind?

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

Which AI models can use Btw?

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 Btw?

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

Is the Btw AI skill free?

Yes. It is published on GitHub by ww-w-ai under the Apache-2.0 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.

Related AI Skills

View all
obra logo

Receiving Code Review

obra
CommunityPopular

Use when receiving code review feedback, before implementing suggestions, especially if feedback seems unclear or technically questionable - requires technical rigor and verification, not performative…

25.8K
288.1K
Instructions
View
obra logo

Requesting Code Review

obra
CommunityPopular

Use when completing tasks, implementing major features, or before merging to verify work meets requirements

25.8K
288.1K
1 files
View
obra logo

Systematic Debugging

obra
CommunityPopular

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes

25.8K
288.1K
10 files
View
obra logo

Test Driven Development

obra
CommunityPopular

Use when implementing any feature or bugfix, before writing implementation code

25.8K
288.1K
1 files
View

Set up your own AI workspace now

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