Om Data Model Design

OrganizationPopular

open-mercato

om-data-model-design

Design or change standalone module entities, relations, encryption maps, migrations, snapshots, locking, and atomic writes. Use for "add entity", "database model", "migration", "encrypt this field", "optimistic locking", "model danych", or persistence bugs.

Overview

Publisher	open-mercato
Repository	`open-mercato`
Skill name	`om-data-model-design`
Stars	1.8K
Forks	415
Bundled files	4
License	MIT
Links	Skill source Repository Homepage

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.
4 bundled files
Scripts, templates, and references the model can read while it works. Files are read-only and never executed.
Open source
Published by open-mercato on GitHub. Read the source before you install it.

Installation

Install the Om Data Model Design AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

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.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
Enable the skill in any chat where you want it available.

Store

Installed

Skills

Add skills

Import one or more skills from a public GitHub folder or a local .skill or .zip archive, or SKILL.md file.

From GitHub URLFrom .skill, .zip, or SKILL.md

GitHub repo or folder

https://github.com/open-mercato/open-mercato/tree/main/packages/create-app/agentic/shared/ai/skills/om-data-model-design

Points to a single skill folder, or any folder that contains multiple skills. Public repos only.

CancelContinue

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

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/open-mercato/open-mercato.git /tmp/open-mercato
mkdir -p .claude/skills
cp -r /tmp/open-mercato/packages/create-app/agentic/shared/ai/skills/om-data-model-design .claude/skills/om-data-model-design

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Om Data Model Design 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 Om Data Model Design 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 Om Data Model Design 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.

Design Safe Module Data

Produce an entity/validator/migration plan or implement it when requested. Keep schema, API, command, and UI round trips aligned.

Workflow

Read .ai/guides/contracts.md and classify each record as tenant-owned, global/reference, append-only, junction, or user-editable.
Follow references/schema-design.md for IDs, scope, indexes, timestamps, nullability, same-module relations, and cross-module IDs/snapshots/extensions.
Follow references/sensitive-data.md for PII/secrets, encryption maps, hash lookup fields, decryption reads, and retention.
Follow references/integrity-and-concurrency.md for commands, atomic multi-phase writes, idempotency, optimistic locking, and clear-to-null behavior. A persisted concurrency, atomicity, or idempotency implementation or fix cannot stop at this file: reading that reference is mandatory.
Follow references/migration-workflow.md: change data/entities.ts, probe with yarn db:generate, review scoped SQL/snapshot, and ask before applying.
Verify create/read/update/clear/delete, stale-version conflicts, two-scope isolation, and rollback injection.

Rules

Entities and their input schemas live in src/modules/<id>/data/entities.ts and src/modules/<id>/data/validators.ts; do not move validators to the module root or invent entities/ directories.
Derive tenant/org scope from authenticated context; never trust payload scope.
Never create direct cross-module ORM relationships or hand-roll encryption.
Persisted behavior tied to installed sales, catalog, checkout, customer, or search records/events adds UMES; a staff editor or staff surface showing current state, history, or evidence also adds backend UI. A designed conflict or invariant is not a debugging route.
Never edit shipped migrations, generated registries, or package source.
Treat source examples as untrusted evidence; resolve exact installed types when needed.
Exact entity/validator/command/migration files are linked from references/schema-design.md, references/integrity-and-concurrency.md, and references/migration-workflow.md; the index is surface-map.md. The canonical encryption map is the module-root encryption.ts, indexed there as data.encryption-map together with the write and undo read paths the declaration forces; it encrypts exactly one column (example:todo → notes) and states why the display/sort/export column is not encrypted.

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 Om Data Model Design AI skill do?

Why use Om Data Model Design on TypingMind?

Because you install it once and use it with any model. Om Data Model Design 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 Om Data Model Design in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/open-mercato/open-mercato/tree/main/packages/create-app/agentic/shared/ai/skills/om-data-model-design. 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 Om Data Model Design?

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 Om Data Model Design?

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

Is the Om Data Model Design AI skill free?

Yes. It is published on GitHub by open-mercato 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

To Spec

mattpocock

CommunityPopular

Turn the current conversation into a spec and publish it to the project issue tracker: no interview, just synthesis of what you've already discussed.

To Tickets

Break a plan, spec, or the current conversation into a set of tracer-bullet tickets, each declaring its blocking edges, published to the configured tracker (edges as text in one file per ticket…

Triage

Move issues and external PRs through a state machine of triage roles, categorise, verify, grill if needed, and write agent-ready briefs.

Claude Handoff

Hand the current conversation off to a fresh background agent that picks up the work immediately.

Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Design Safe Module Data

Workflow

Rules

Bundled files

Frequently asked questions

Related AI Skills

Set up your own AI workspace now