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Dive Tag

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iantbutler01
dive-tag

Add structured @dive comments and maintain .dive metadata so code changes are explainable and navigable.

Overview

Publisheriantbutler01
Repositorycode_diver
Skill namedive-tag
Stars
76
Forks
4
Bundled files
Instructions only
LicenseApache-2.0
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 iantbutler01 on GitHub. Read the source before you install it.

Installation

Install the Dive Tag 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/iantbutler01/code_diver/tree/main/skills/dive-tag
  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/iantbutler01/code_diver.git /tmp/code_diver
mkdir -p .claude/skills
cp -r /tmp/code_diver/skills/dive-tag .claude/skills/dive-tag
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Dive Tag 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 Dive Tag 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 Dive Tag 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.

Dive Tag

Goal

Maintain a lightweight, cumulative knowledge graph while coding by:

  1. Adding @dive comments near meaningful logic
  2. Maintaining project metadata in .dive/overview.md and .dive/modules/*.md

Use this skill automatically whenever you modify code.

Required Outputs

1) File-level headers

At the top of any source file you create or substantially modify, add:

text
@dive-file: <what this file is responsible for>
@dive-rel: <relationship to another file/module/dependency>
@dive-rel: <another relationship, if relevant>

Comment syntax must match the language:

  • Rust/JS/TS/Go/Java/C/C++/C#: //
  • Python/Shell/Ruby/YAML/TOML: #
  • HTML/XML/Markdown: <!-- -->

Examples:

rust
// @dive-file: Validates JWT tokens and creates auth context for requests.
// @dive-rel: Called by src/api/middleware.rs for every authenticated route.
// @dive-rel: Uses src/auth/session.rs to reject revoked sessions.

2) Inline tags

Add @dive: comments for non-trivial logic you write or change.

Format:

text
@dive: <plain-English behavior and outcome>

Good:

  • @dive: Normalizes user input so lookup is case-insensitive
  • @dive: Retries DB write once when the first attempt times out

Avoid:

  • Restating syntax
  • Vague notes like "does stuff"
  • Tagging every trivial line

3) System metadata

Create/update .dive/overview.md at the project root.

Required structure:

markdown
# System Overview
<brief system description>

## Components
- **<Component>** - <responsibility> -> <path>

## Relationships
- <Component A> -> <Component B>: <how they interact>

4) Module metadata

Create/update .dive/modules/<module>.md for modules affected by your changes.

Required structure:

markdown
# <Module> Module
<module purpose>

## Files
- `<relative/path>` - <file responsibility>

## Relationships
- <file A> -> <file B>: <dependency or call flow>

Operating Rules

  1. Keep paths project-relative (for example src/auth/jwt.rs).
  2. Update metadata incrementally when behavior changes.
  3. Preserve existing useful entries; refine instead of replacing wholesale.
  4. Prefer directional relationships (A -> B or A <- B) with short context.
  5. If .dive/ does not exist, create it with overview.md and modules/.
  6. If uncertain, write conservative descriptions and avoid guessing internals.

Minimal Workflow

  1. Read existing .dive/overview.md and relevant .dive/modules/*.md if present.
  2. Implement code changes.
  3. Add/update file headers and inline @dive: tags in touched files.
  4. Update .dive/overview.md if component boundaries or interactions changed.
  5. Update relevant .dive/modules/*.md for touched files and relationships.

Completion Checklist

  • Touched files include accurate @dive-file and @dive-rel headers
  • New or changed logic includes meaningful @dive: comments
  • .dive/overview.md exists and reflects current component structure
  • .dive/modules/*.md exists for touched modules and links to real files

Frequently asked questions

What does the Dive Tag AI skill do?

Add structured @dive comments and maintain .dive metadata so code changes are explainable and navigable.

Why use Dive Tag on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/iantbutler01/code_diver/tree/main/skills/dive-tag. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Dive Tag?

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 Dive Tag?

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

Is the Dive Tag AI skill free?

Yes. It is published on GitHub by iantbutler01 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.

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