Content Modeling Best Practices
sanity-io/agent-toolkit
Structured content modeling guidance for schema design, content architecture, content reuse, references versus embedded objects, separation of concerns, and taxonomies across Sanity and other…
Define backend data modeling standards for Python services. An agent skill from AUTO-MAS-Project/AUTO-MAS.
$ npx skills add AUTO-MAS-Project/AUTO-MAS --skill mas-data-model -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install AUTO-MAS-Project/AUTO-MAS mas-data-model --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/AUTO-MAS-Project/AUTO-MAS.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/mas-data-model .claude/skills/mas-data-model && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "mas-data-model" agent skill from https://github.com/AUTO-MAS-Project/AUTO-MAS/tree/main/.agents/skills/mas-data-model into .claude/skills/mas-data-model/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "mas-data-model", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/AUTO-MAS-Project/AUTO-MAS/tree/main/.agents/skills/mas-data-modelType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add AUTO-MAS-Project/AUTO-MAS --skill mas-data-model -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install AUTO-MAS-Project/AUTO-MAS mas-data-model --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/AUTO-MAS-Project/AUTO-MAS.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.agents/skills/mas-data-model .agents/skills/mas-data-model && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "mas-data-model" agent skill from https://github.com/AUTO-MAS-Project/AUTO-MAS/tree/main/.agents/skills/mas-data-model into .agents/skills/mas-data-model/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "mas-data-model", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add AUTO-MAS-Project/AUTO-MAS --skill mas-data-model -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install AUTO-MAS-Project/AUTO-MAS mas-data-model --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/AUTO-MAS-Project/AUTO-MAS.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.agents/skills/mas-data-model .cursor/skills/mas-data-model && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "mas-data-model" agent skill from https://github.com/AUTO-MAS-Project/AUTO-MAS/tree/main/.agents/skills/mas-data-model into .cursor/skills/mas-data-model/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "mas-data-model", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/AUTO-MAS-Project/AUTO-MAS.git --path .agents/skills/mas-data-model--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add AUTO-MAS-Project/AUTO-MAS --skill mas-data-model -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install AUTO-MAS-Project/AUTO-MAS mas-data-model --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/AUTO-MAS-Project/AUTO-MAS.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.agents/skills/mas-data-model .gemini/skills/mas-data-model && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "mas-data-model" agent skill from https://github.com/AUTO-MAS-Project/AUTO-MAS/tree/main/.agents/skills/mas-data-model into .gemini/skills/mas-data-model/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "mas-data-model", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install AUTO-MAS-Project/AUTO-MAS mas-data-modelInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add AUTO-MAS-Project/AUTO-MAS --skill mas-data-model -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/AUTO-MAS-Project/AUTO-MAS.git skills-src && mkdir -p .github/skills && cp -r skills-src/.agents/skills/mas-data-model .github/skills/mas-data-model && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "mas-data-model" agent skill from https://github.com/AUTO-MAS-Project/AUTO-MAS/tree/main/.agents/skills/mas-data-model into .github/skills/mas-data-model/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "mas-data-model", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add AUTO-MAS-Project/AUTO-MAS --skill mas-data-model -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install AUTO-MAS-Project/AUTO-MAS mas-data-model --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/AUTO-MAS-Project/AUTO-MAS.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.agents/skills/mas-data-model .opencode/skills/mas-data-model && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "mas-data-model" agent skill from https://github.com/AUTO-MAS-Project/AUTO-MAS/tree/main/.agents/skills/mas-data-model into .opencode/skills/mas-data-model/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "mas-data-model", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
mas-data-modelDefine backend data modeling standards for Python services. An agent skill from AUTO-MAS-Project/AUTO-MAS.
Mas Data Model is an agent skill from AUTO-MAS-Project/AUTO-MAS. Define backend data modeling standards for Python services. Use when designing or refactoring models in app/models (schema/config/task), normalizing shared fields, choosing types/defaults/validation strategy, and evolving model contracts with backward compatibility.
Its SKILL.md is about 1.6k tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files (for example `agents/openai.yaml`).
It sits in Databases, covering Database schema design and Refactoring. It works with Python. The repository describes itself as: 多脚本多配置统一管理与自动化工具 | 轻松管理大量脚本并存储多个用户配置、设计自动化任务流、监看脚本日志,大幅提高自动化代理效率与稳定性!. The licence is AGPL-3.0.
3 steps, taken from the first numbered list in SKILL.md.
Read from SKILL.md and the folder at commit 699de5a. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
No scripts in the folder and no shell commands in SKILL.md.
From the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Mas Data Model loads about 1.6k tokens when it runs. Until then it costs about 70 tokens; SKILL.md has 829 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
The full file from AUTO-MAS-Project/AUTO-MAS at commit 699de5a, republished under its AGPL-3.0 licence (© AUTO-MAS-Project). 829 words, ~1,597 tokens.
.claude/skills/mas-data-model/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.Build backend data models that are explicit, consistent, and evolution-friendly.
Apply to model definitions under app/models:
schema)config, ConfigBase)task)schema models define external API contracts only.config models define persisted configuration structure and validation behavior.task models define runtime execution state and orchestration-facing status.ConfigBase subclasses define real persisted config templates; every ConfigItem must be declared before super().__init__() to be indexed, settable, and saved.MultipleConfig represents a dictionary-like collection of ConfigBase instances and must be declared with all allowed concrete config classes.Info, Run, Notify, Data).mas-schema-naming.Any.Literal or explicit enums for bounded value sets.default_factory when mutable).None defaults only for truly optional semantics.uuid existence.RangeValidator, OptionsValidator, BoolValidator, path validators, EncryptValidator, VirtualConfigValidator, and MultipleUIDValidator can rewrite stored values.VirtualConfigValidator(function) for computed display/config fields that should be read through normal config access but must not be set or persisted as user input.scriptId, userId, queueId).password, token, key).Dict[str, Any] replacing known structured fields.super().__init__() and expecting them to participate in normal config load/save behavior.GlobalConfig collection, CLASS_BOOK/registry entry, schema type, or API handling.schema/config/task).mas-module-boundary and API usage follows mas-api-contract.ConfigItem with nearby comments and are grouped by Info, Run, Task, Data, Notify, or the local domain grouping used by neighbors.MultipleConfig([...]) and any needed UID-reference field points at the owning collection.© AUTO-MAS-Project, AGPL-3.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
SKILL.md and 1 other file in .agents/skills/mas-data-model of AUTO-MAS-Project/AUTO-MAS.
Open the folder on GitHubat commit 699de5a
Mas Data Model next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Mas Data Model this skillAUTO-MAS-Project/AUTO-MAS | 708 | — | ~1.6k | Automated safety check: Pass | AGPL-3.0 | |
| Content Modeling Best Practicessanity-io/agent-toolkit | 188 | 1 repos | ~463 | Automated safety check: Pass | MIT | |
| Saleor Django Migration Rulessaleor/saleor | 23k | — | ~1.6k | Automated safety check: Pass | BSD-3-Clause | |
| Add Mpk Taskmirage-project/mirage | 2.5k | — | ~4.5k | Automated safety check: Pass | Apache-2.0 | |
| Effect TSmattiacerutti/supernova | 187 | — | ~2.8k | Automated safety check: Pass | MIT | |
| SQL Schema Policy Validatorrominirani/antigravity-skills | 592 | — | ~264 | Automated safety check: Pass | None |
sanity-io/agent-toolkit
Structured content modeling guidance for schema design, content architecture, content reuse, references versus embedded objects, separation of concerns, and taxonomies across Sanity and other…
saleor/saleor
Rules for writing Django migrations in Saleor that avoid long table locks and stay compatible with zero-downtime rolling deploys.
mirage-project/mirage
Step-by-step guide for adding a new task implementation to Mirage Persistent Kernel (MPK).
mattiacerutti/supernova
Write idiomatic Effect v4 TypeScript following official best practices from effect-solutions and the Effect source.
rominirani/antigravity-skills
Validates SQL schema files for compliance with internal safety and naming policies.
tellahq/opensession
Write idiomatic Effect v4 TypeScript verified against the pinned effect@4.0.0-rc.112 source.
AUTO-MAS-Project/AUTO-MAS
Add, refactor, or review AUTO-MAS game community sign-in (game sign) code, including the provider registry in app/tools/gamesign.py, platform adapters for Skland/Miyoushe/Kuro/Taygedo, credential…
AUTO-MAS-Project/AUTO-MAS
Define canonical naming for future backend schema domains. An agent skill from AUTO-MAS-Project/AUTO-MAS.
AUTO-MAS-Project/AUTO-MAS
A skill your agent uses when implementing, fixing, refactoring, or reviewing non-generated AUTO-MAS code, or when preparing code-style guidance, comments, docstrings, version notes, or Conventional…
AUTO-MAS-Project/AUTO-MAS
A skill your agent uses when working on AUTO-MAS frontend UI, Ant Design Vue components, page layout, forms, tables, modals, drawers, feedback, empty/loading/error states, drag interactions, dark…
AUTO-MAS-Project/AUTO-MAS
Review, add, or refactor AUTO-MAS specialized script adapters by upstream architecture, including MAA, SRC, MaaEnd/MXU, General, ok-script adapters such as Okww and OkNte, multi-engine adapters such…
AUTO-MAS-Project/AUTO-MAS
Define backend API contract standards for FastAPI services. An agent skill from AUTO-MAS-Project/AUTO-MAS.
Works with
Categories
Define backend data modeling standards for Python services. An agent skill from AUTO-MAS-Project/AUTO-MAS. Mas Data Model is an agent skill from AUTO-MAS-Project/AUTO-MAS. Define backend data modeling standards for Python services.
Mas Data Model fits situations like: refactoring models in app/models (schema/config/task); normalizing shared fields; choosing types/defaults/validation strategy; evolving model contracts with backward compatibility.
Run `npx skills add AUTO-MAS-Project/AUTO-MAS --skill mas-data-model -a claude-code`. Or copy the skill folder (.agents/skills/mas-data-model in AUTO-MAS-Project/AUTO-MAS) into .claude/skills/mas-data-model in your project. Claude Code loads it when a task matches its description.
Run `npx skills add AUTO-MAS-Project/AUTO-MAS --skill mas-data-model -a codex`. Or copy the skill folder (.agents/skills/mas-data-model in AUTO-MAS-Project/AUTO-MAS) into .agents/skills/mas-data-model in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add AUTO-MAS-Project/AUTO-MAS --skill mas-data-model -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/mas-data-model, .gemini/skills/mas-data-model, .github/skills/mas-data-model and .opencode/skills/mas-data-model in your project.
SKILL.md names no scripts, command-line tools or credentials: Mas Data Model is instructions for the agent only. Our summary lists: Python 3.
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
Mas Data Model is published under the AGPL-3.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 1.6k tokens (SKILL.md is roughly 6.4k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with Mas Data Model: Content Modeling Best Practices (sanity-io/agent-toolkit, 188 stars), Saleor Django Migration Rules (saleor/saleor, 23k stars), Add Mpk Task (mirage-project/mirage, 2.5k stars) and Effect TS (mattiacerutti/supernova, 187 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
AUTO-MAS-Project (a GitHub organization) maintains it in AUTO-MAS-Project/AUTO-MAS, which has 708 GitHub stars. The repository holds 15 skills in this directory. The repository was last updated on October 8, 2026.
Source: AUTO-MAS-Project/AUTO-MAS on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.