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Mino Domain Model Completeness

Community
my-take-dev
mino-domain-model-completeness

固定したユースケースで用語・概念・値制約・状態・遷移・失敗・時間・writer/reader・authorityの欠落を監査するときに使う。世界全体のモデル化、図だけ、一般DDD解説、単なるデータ項目一覧には使わない。

Overview

Publishermy-take-dev
Repositoryinspired-mino-design-skills
Skill namemino-domain-model-completeness
Stars
345
Forks
9
Bundled files
2
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.

  • 2 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by my-take-dev on GitHub. Read the source before you install it.

Installation

Install the Mino Domain Model Completeness 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/my-take-dev/inspired-mino-design-skills/tree/main/.agents/skills/mino-domain-model-completeness
  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/my-take-dev/inspired-mino-design-skills.git /tmp/inspired-mino-design-skills
mkdir -p .claude/skills
cp -r /tmp/inspired-mino-design-skills/.agents/skills/mino-domain-model-completeness .claude/skills/mino-domain-model-completeness
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Mino Domain Model Completeness 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 Mino Domain Model Completeness 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 Mino Domain Model Completeness 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.

Domain Model Completeness

Outcome Contract

固定したuse caseの要件・model・経路の欠落と、契約・testへ渡すobligationを返す。screeningとmodelの実在coverageを分ける。 正本packageのrootはcompleteness_package。 対応mode: design, review。

Reference Routing

  • 初回はskills/mino-core/references/shared-policies.mdを読み、Evidence・承認・判定を適用する。同じcontextで既読なら再読しない。通常の判断は本体とこの共通規則で行う。
  • 用語・context・暗黙概念の欠落が判断を分けるときはskills/mino-core/references/domain-discovery.mdを読み、同じ例で意味差を検証する。
  • 対象systemのfile/process/test実行・複数OS要件がある場合はskills/mino-core/references/platform-compatibility.mdを読み、host・対象・検証層を分ける。単なる回答記録の保存では追加読込しない。
  • 正本packageの作成・更新・引継ぎを依頼された場合だけskills/mino-domain-model-completeness/schemas/package.mdを読み、必須fieldと実在参照を保持する。

Workflow

  1. actor、use case、context、要件、対象外を固定する。DB項目や既存名詞だけで必要概念を決めない。
  2. 各要件のterm_context、concept、constraint、state、transition、behavior、relationship、failure、time、writer、reader、authorityの12観点を一度ずつscreenする。各cellをEvidence付きmodel elementへのlinkか理由付きN/Aにする。同じ理由・EvidenceのN/Aだけprofileを共有できる。
  3. 必要だがない要素はmissing、未確認はunknown、矛盾はconflictingとして区別する。要件に定義があることと、対象modelに実在・保証されることを分ける。presentには監査対象の定義・code・観測へのEvidenceを要し、要求だけを根拠に充足へ数えない。未知はN/Aにしない。concept_kindはconceptだけに使う。
  4. constructor/setter、serializer、永続化、API/event、batch/admin、import、migration、手作業を探索候補として、scopeへ到達するwriter / readerを追う。実在経路と未探索領域を分け、提供資料にない経路の存在・不在を捏造しない。
  5. 意味のowner、不変条件のowner、状態遷移のauthority、状態の正本を区別する。各writerの迂回、readerの誤解釈、UI/adapterへの業務規則の漏出、関係ごとの失敗意味を確認する。system全体の選定は参照・obligationにとどめる。移行中の複数writerは期間・競合規則・照合・削除条件・ownerを要する。
  6. 思考実験か使い捨てfixtureでentry→破壊入力・順序→伝播→業務影響→期待不変条件を追う。境界値、null、禁止組合せ、遷移skip/逆行、並行writer、stale reader、外部成功/内部失敗から該当する反例を選ぶ。観測結果と防御を独立判定する。
  7. 必要な契約・testにはそれぞれCO / TO obligationを付ける。下流が未作成ならCI / T IDを発行せず、実在する場合だけ接続する。
  8. screen分母=要件数×12、分子=根拠付きlink/N/Aで処遇を記録したcell数。未知もunknownなmodel elementへ接続し、何が未確認かを根拠付きで記録すればscreen済みに数える。model分母=N/A以外のcell数、分子=必要elementが全てpresentかつunknown/contradictionでないEvidenceを持つcell数。missing/unknown/conflictingをpresentへ数えない。

Hard Gates

  • 表が埋まったことをmodel completeとしない。未確認writer・readerや迂回経路を監査済みにしない。
  • 本番dataへ破壊probeを行わない。未実行はnot_executedでありpreventedではない。必要なprobeは契約とtest両方のobligationへ接続する。
  • 対象code・運用dataは変更しない。修正依頼は権限を保った引継ぎにする。

Completion

固定scopeの必要modelと経路が根拠付きで揃えばcomplete、既知gapがあればincomplete、重要未確認で判断できなければindeterminate。既知gapと未知の併存はincompleteとして両方を返す。監査artifactは欠陥を報告してreadyになり得る。

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Mino Domain Model Completeness AI skill do?

固定したユースケースで用語・概念・値制約・状態・遷移・失敗・時間・writer/reader・authorityの欠落を監査するときに使う。世界全体のモデル化、図だけ、一般DDD解説、単なるデータ項目一覧には使わない。

Why use Mino Domain Model Completeness on TypingMind?

Because you install it once and use it with any model. Mino Domain Model Completeness 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 Mino Domain Model Completeness in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/my-take-dev/inspired-mino-design-skills/tree/main/.agents/skills/mino-domain-model-completeness. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Mino Domain Model Completeness?

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 Mino Domain Model Completeness?

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

Is the Mino Domain Model Completeness AI skill free?

It is published on GitHub by my-take-dev. Check the repository for licensing terms. 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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