Agent skill

Mas Schema Naming

by AUTO-MAS-Project in AUTO-MAS-Project/AUTO-MAS

Define canonical naming for future backend schema domains. An agent skill from AUTO-MAS-Project/AUTO-MAS.

AGPL-3.0Auto-check passed

Install Mas Schema Naming

skills CLI

$ npx skills add AUTO-MAS-Project/AUTO-MAS --skill mas-schema-naming -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI

$ gh skill install AUTO-MAS-Project/AUTO-MAS mas-schema-naming --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy

$ 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-schema-naming .claude/skills/mas-schema-naming && rm -rf skills-src

Use ~/.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/

Paste into Claude Code

Install the "mas-schema-naming" agent skill from https://github.com/AUTO-MAS-Project/AUTO-MAS/tree/main/.agents/skills/mas-schema-naming into .claude/skills/mas-schema-naming/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "mas-schema-naming", 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

$skill-installer install https://github.com/AUTO-MAS-Project/AUTO-MAS/tree/main/.agents/skills/mas-schema-naming

Type 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.

skills CLI

$ npx skills add AUTO-MAS-Project/AUTO-MAS --skill mas-schema-naming -a codex

Project install goes to .agents/skills/; add -g for ~/.codex/skills/.

GitHub CLI

$ gh skill install AUTO-MAS-Project/AUTO-MAS mas-schema-naming --agent codex

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ 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-schema-naming .agents/skills/mas-schema-naming && rm -rf skills-src

Use ~/.agents/skills/ instead of .agents/skills for a personal install.

Codex skills documentation · loads skills from .agents/skills/

Paste into Codex

Install the "mas-schema-naming" agent skill from https://github.com/AUTO-MAS-Project/AUTO-MAS/tree/main/.agents/skills/mas-schema-naming into .agents/skills/mas-schema-naming/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "mas-schema-naming", 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.

skills CLI

$ npx skills add AUTO-MAS-Project/AUTO-MAS --skill mas-schema-naming -a cursor

Project install goes to .agents/skills/; add -g for ~/.cursor/skills/.

GitHub CLI

$ gh skill install AUTO-MAS-Project/AUTO-MAS mas-schema-naming --agent cursor

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ 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-schema-naming .cursor/skills/mas-schema-naming && rm -rf skills-src

Use ~/.cursor/skills/ instead of .cursor/skills for a personal install.

Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/

Paste into Cursor

Install the "mas-schema-naming" agent skill from https://github.com/AUTO-MAS-Project/AUTO-MAS/tree/main/.agents/skills/mas-schema-naming into .cursor/skills/mas-schema-naming/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "mas-schema-naming", 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

$ gemini skills install https://github.com/AUTO-MAS-Project/AUTO-MAS.git --path .agents/skills/mas-schema-naming

--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.

skills CLI

$ npx skills add AUTO-MAS-Project/AUTO-MAS --skill mas-schema-naming -a gemini-cli

Project install goes to .agents/skills/; add -g for ~/.gemini/skills/.

GitHub CLI

$ gh skill install AUTO-MAS-Project/AUTO-MAS mas-schema-naming --agent gemini-cli

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ 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-schema-naming .gemini/skills/mas-schema-naming && rm -rf skills-src

Use ~/.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/

Paste into Gemini CLI

Install the "mas-schema-naming" agent skill from https://github.com/AUTO-MAS-Project/AUTO-MAS/tree/main/.agents/skills/mas-schema-naming into .gemini/skills/mas-schema-naming/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "mas-schema-naming", 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.

GitHub CLI

$ gh skill install AUTO-MAS-Project/AUTO-MAS mas-schema-naming

Installs 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).

skills CLI

$ npx skills add AUTO-MAS-Project/AUTO-MAS --skill mas-schema-naming -a github-copilot

Project install goes to .agents/skills/; add -g for ~/.copilot/skills/.

Manual copy

$ 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-schema-naming .github/skills/mas-schema-naming && rm -rf skills-src

Use ~/.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/

Paste into GitHub Copilot

Install the "mas-schema-naming" agent skill from https://github.com/AUTO-MAS-Project/AUTO-MAS/tree/main/.agents/skills/mas-schema-naming into .github/skills/mas-schema-naming/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "mas-schema-naming", 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.

skills CLI

$ npx skills add AUTO-MAS-Project/AUTO-MAS --skill mas-schema-naming -a opencode

OpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.

GitHub CLI

$ gh skill install AUTO-MAS-Project/AUTO-MAS mas-schema-naming --agent opencode

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ 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-schema-naming .opencode/skills/mas-schema-naming && rm -rf skills-src

Use ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.

OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/

Paste into OpenCode

Install the "mas-schema-naming" agent skill from https://github.com/AUTO-MAS-Project/AUTO-MAS/tree/main/.agents/skills/mas-schema-naming into .opencode/skills/mas-schema-naming/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "mas-schema-naming", 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.

Facts

Skill name: mas-schema-naming
GitHub stars: 711
Token cost: ~1k tokens
SKILL.md length: 427 words
Files: 2
Skills in repo: 15
Repo updated: Oct 10, 2026
First seen: Oct 7, 2026
Licence: AGPL-3.0

At a glance

Define canonical naming for future backend schema domains. An agent skill from AUTO-MAS-Project/AUTO-MAS.

Works in 4 steps: Make minimal necessary changes first;… → Align with current code style and… → Avoid over-engineering,… → …
Creating new specialized schema models
SKILL.md covers Objective, Global Constraints, Apply Workflow and Canonical Structure For New…, plus 5 more sections
Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Mas Schema Naming is an agent skill from AUTO-MAS-Project/AUTO-MAS. Define canonical naming for future backend schema domains. Use when creating new specialized schema models or extending Pydantic contracts in app/models/schema.py, standardizing shared Info/Data/Notify/Run semantics, and avoiding new naming drift without forcing retroactive changes on legacy modules.

Its SKILL.md is about 1k tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files (for example `agents/openai.yaml`).

It works with Pydantic. 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.

When your agent uses it

Creating new specialized schema models
Extending Pydantic contracts in app/models/schema.py
Standardizing shared Info/Data/Notify/Run semantics
Avoiding new naming drift without forcing retroactive changes on legacy modules

Example prompts

“/mas-schema-naming”

Requirements

Python 3

Workflow steps

4 steps, taken from the first numbered list in SKILL.md.

Make minimal necessary changes first; avoid broad refactors unless explicitly requested.
Align with current code style and existing project conventions in the touched module.
Avoid over-engineering, over-abstraction, and defensive programming that does not match existing code patterns.
Study similar existing implementations deeply before coding and follow established local patterns.

What it can do on your machine

Read from SKILL.md and the folder at commit 699de5a. It shows what the files ask for, not the result of running them.

Tool permissions
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.
Runs code
No scripts in the folder and no shell commands in SKILL.md (its code samples are python).
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Mas Schema Naming loads about 1k tokens when it runs. Until then it costs about 80 tokens; SKILL.md has 427 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it: ~80
When it runs · the whole SKILL.md, loaded when a task matches: ~1k

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.

Safety

Auto-check passed

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.

SKILL.md

The full file from AUTO-MAS-Project/AUTO-MAS at commit 699de5a, republished under its AGPL-3.0 licence (© AUTO-MAS-Project). 427 words, ~1,039 tokens.

Download SKILL.mdSave it as .claude/skills/mas-schema-naming/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.

name: mas-schema-naming
description: Define canonical naming for future backend schema domains. Use when creating new specialized schema models or extending Pydantic contracts in app/models/schema.py, standardizing shared Info/Data/Notify/Run semantics, and avoiding new naming drift without forcing retroactive changes on legacy modules.

MAS Schema Naming

Objective

Standardize naming for future specialized backend schema implementations.

This skill constrains new domain work by default. It does not require retroactive renaming of existing legacy modules unless explicitly requested.

Global Constraints

Apply these constraints while using this skill.

Make minimal necessary changes first; avoid broad refactors unless explicitly requested.
Align with current code style and existing project conventions in the touched module.
Avoid over-engineering, over-abstraction, and defensive programming that does not match existing code patterns.
Study similar existing implementations deeply before coding and follow established local patterns.

Apply Workflow

Determine whether the field is shared semantic or domain-specific semantic.
For shared semantic, use the canonical name from this skill.
For domain-specific semantic, keep naming local to the domain block.
Keep public config-model field style consistent: PascalCase.
When touching legacy modules, prefer compatibility-first edits and avoid broad rename-only refactors.

Canonical Structure For New Domains

Use this top-level structure for new script/user schema models.

python

class XxxConfig(BaseModel):
    Info: XxxConfig_Info | None
    Run: XxxConfig_Run | None
    Emulator: XxxConfig_Emulator | None  # only if emulator semantics exist


class XxxUserConfig(BaseModel):
    Info: XxxUserConfig_Info | None
    Data: XxxUserConfig_Data | None
    Notify: XxxUserConfig_Notify | None
    # optional domain blocks, e.g. Task/Stage/Game

Shared Naming Matrix

Use these names when semantics are the same.

Semantic	Canonical name	Block
Script display name	`Name`	`Info`
Script runtime path	`Path`	`Info`
Emulator id	`Id`	`Emulator`
Emulator index	`Index`	`Emulator`
Transition strategy	`TaskTransitionMethod`	`Run`
Daily proxy limit	`ProxyTimesLimit`	`Run`
Retry limit	`RunTimesLimit`	`Run`
Runtime timeout	`RunTimeLimit`	`Run`
User display name	`Name`	`User.Info`
User id	`Id`	`User.Info`
User enabled status	`Status`	`User.Info`
Remaining day budget	`RemainedDay`	`User.Info`
User note	`Notes`	`User.Info`
User tag payload	`Tag`	`User.Info`
Last proxy date	`LastProxyDate`	`User.Data`
Proxy run count	`ProxyTimes`	`User.Data`
Manual-check result	`IfPassCheck`	`User.Data`
Notify enabled	`Enabled`	`User.Notify`
Send statistic	`IfSendStatistic`	`User.Notify`
Send mail	`IfSendMail`	`User.Notify`
Mail receiver	`ToAddress`	`User.Notify`
ServerChan enabled	`IfServerChan`	`User.Notify`
ServerChan key	`ServerChanKey`	`User.Notify`

Show full SKILL.md (146 more words)Show less

Boundary For Domain-Specific Names

Keep domain-specific semantics inside dedicated domain blocks.
Do not force shared naming when semantics differ.
Do not add synonym fields for the same semantic in one block.

Drift To Avoid In New Work

Same semantic, different names (Path vs RootPath).
Same semantic, different block placement (Data vs Info).
Same semantic, mixed boolean style in the same block.

Compatibility Rule

When canonicalizing an existing public field:

Keep read compatibility for legacy payloads during migration.
Prefer writing canonical names in new responses.
Remove legacy names only after consumer migration is complete.

PR Checklist

New specialized schema models follow this canonical matrix for shared semantics.
Domain-specific fields stay in domain-specific blocks.
No new synonym names are introduced for existing shared semantics.
Legacy modules are not renamed in bulk unless explicitly in scope.

Files

SKILL.md and 1 other file in .agents/skills/mas-schema-naming of AUTO-MAS-Project/AUTO-MAS.

SKILL.md
agents/openai.yaml

Open the folder on GitHubat commit 699de5a

Compare with similar skills

Mas Schema Naming 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.

Mas Schema Naming compared with similar skills
Skill	Stars	Used in	Tokens	Auto-check	Licence	Repo updated
Mas Schema Naming this skillAUTO-MAS-Project/AUTO-MAS	711	—	~1k	Automated safety check: Pass	AGPL-3.0	today
Building Pydantic AI Agentsdocling-project/docling	69k	—	~2.8k	Automated safety check: Pass	MIT	today
Datachain Knowledgedatachain-ai/datachain	2.8k	—	~3k	Automated safety check: Pass	Apache-2.0	today
Fastcrudbenavlabs/fastcrud	1.6k	—	~5k	Automated safety check: Pass	MIT	16 days ago
Building Pydantic AI Agentspydantic/pydantic-ai	21k	—	~8.2k	Automated safety check: Pass	MIT	today
Investor Panel Stock Reviewwbh604/UZI-Skill	7.1k	—	~757	Automated safety check: Pass	MIT	1 mo ago

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Works with

Pydantic

Questions about Mas Schema Naming

What does Mas Schema Naming do?

Define canonical naming for future backend schema domains. An agent skill from AUTO-MAS-Project/AUTO-MAS. Mas Schema Naming is an agent skill from AUTO-MAS-Project/AUTO-MAS. Define canonical naming for future backend schema domains.

When should I use Mas Schema Naming?

Mas Schema Naming fits situations like: creating new specialized schema models; extending Pydantic contracts in app/models/schema.py; standardizing shared Info/Data/Notify/Run semantics; avoiding new naming drift without forcing retroactive changes on legacy modules.

How do I install Mas Schema Naming in Claude Code?

Run `npx skills add AUTO-MAS-Project/AUTO-MAS --skill mas-schema-naming -a claude-code`. Or copy the skill folder (.agents/skills/mas-schema-naming in AUTO-MAS-Project/AUTO-MAS) into .claude/skills/mas-schema-naming in your project. Claude Code loads it when a task matches its description.

How do I install Mas Schema Naming in Codex?

Run `npx skills add AUTO-MAS-Project/AUTO-MAS --skill mas-schema-naming -a codex`. Or copy the skill folder (.agents/skills/mas-schema-naming in AUTO-MAS-Project/AUTO-MAS) into .agents/skills/mas-schema-naming in your project. Codex loads it when a task matches its description.

Can I use Mas Schema Naming in Cursor, Gemini CLI or GitHub Copilot?

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-schema-naming -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-schema-naming, .gemini/skills/mas-schema-naming, .github/skills/mas-schema-naming and .opencode/skills/mas-schema-naming in your project.

What does Mas Schema Naming need to run?

SKILL.md names no scripts, command-line tools or credentials: Mas Schema Naming is instructions for the agent only. Our summary lists: Python 3.

Does Mas Schema Naming access the network?

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.

Is Mas Schema Naming safe to install?

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.

What licence does Mas Schema Naming use?

Mas Schema Naming 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.

How many tokens does Mas Schema Naming use?

About 1k tokens (SKILL.md is roughly 4.2k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Mas Schema Naming?

Skills that share tags, products or a category with Mas Schema Naming: Building Pydantic AI Agents (docling-project/docling, 69k stars), Datachain Knowledge (datachain-ai/datachain, 2.8k stars), Fastcrud (benavlabs/fastcrud, 1.6k stars) and Building Pydantic AI Agents (pydantic/pydantic-ai, 21k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Mas Schema Naming?

AUTO-MAS-Project (a GitHub organization) maintains it in AUTO-MAS-Project/AUTO-MAS, which has 711 GitHub stars. The repository holds 15 skills in this directory. The repository was last updated on October 10, 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.

Install Mas Schema Naming

Facts

At a glance

What it does

When your agent uses it

Example prompts

Requirements

Workflow steps

What it can do on your machine

Tool permissions

Runs code

Network

Credentials

Context cost

Safety

SKILL.md

MAS Schema Naming

Objective

Global Constraints

Apply Workflow

Canonical Structure For New Domains

Shared Naming Matrix

Boundary For Domain-Specific Names

Drift To Avoid In New Work

Compatibility Rule

PR Checklist

Files

Compare with similar skills

Similar skills

More from AUTO-MAS-Project/AUTO-MAS

Related

Questions about Mas Schema Naming