Yao Open Prompts Catalog Guide

yao-open-prompts GitHub tool guide thumbnail

TL;DR

TL;DR: yao-open-prompts is a Chinese-first prompt library with an English mirror, catalog files, templates, maintenance scripts, and clear prompt metadata; use it as a curated prompt source, not as a runnable Python app.

Source and Accuracy Notes

This guide uses official material from yaojingang/yao-open-prompts, including README.md, README.en.md, CATALOG.md, repository structure, prompt-file conventions, and maintenance notes. The repo contains Python scripts for checking and generating catalog/web pages, but everyday users do not need to install a Python package. Commands below are limited to commands documented by project files.

Current frontmatter remains unchanged to preserve runany.dev identity. One practical correction for readers: GitHub may label the repo as Python because maintenance scripts exist, but the core artifact is prompt content in Markdown.

What Is yao-open-prompts?

yao-open-prompts is an open prompt library centered on Chinese scenarios, with English prompts kept separately under prompts-en/. It covers work, study, content creation, marketing, education, life, programming, thinking, and AI-method prompts. Instead of shipping an agent, API server, or model, it ships reusable prompt documents plus a catalog and contribution workflow.

The directory structure explains the product. prompts/ contains scenario-based Chinese prompt bodies. prompts-en/ keeps English synchronized prompts without mixing them into Chinese source material. references/ collects recommended resources, third-party content, and external project indexes. templates/ gives prompt templates. maintenance/ stores review and release checklists. scripts/ contains directory generation and quality-check scripts. docs/ publishes prompt-type and representative-prompt pages. CATALOG.md is full prompt index.

This matters because prompt libraries age quickly. Without file conventions, catalogs, and maintenance checks, a prompt repository becomes a pile of snippets. yao-open-prompts makes metadata part of prompt hygiene: title, category, subcategory, source section, author/source, version, creation date, status, and tags.

Repo-Specific Setup Workflow

Step 1: Browse before cloning

Most users should start on GitHub. Open CATALOG.md, scan category names, then open individual prompt files. No runtime is needed if your workflow is copy, adapt, test, and save prompts into your own system.

Step 2: Clone for offline search or contribution

The main project docs emphasize directory use and maintenance commands, not package installation. If you need local search, clone from GitHub using normal Git workflow. The project itself documents maintenance commands rather than a required install command, so keep local setup minimal unless you plan to contribute.

Step 3: Understand repository layout

prompts/                # 按场景分类的提示词正文
prompts-en/             # 英文同步版提示词
references/             # 推荐资源、第三方内容和外部项目索引
templates/              # 新增提示词模板
maintenance/            # 维护、评审、发布检查清单
scripts/                # 目录生成和仓库质量检查脚本
docs/                   # 提示词类型与代表提示词网页
README.en.md            # 英文说明文档
CATALOG.md              # 全量提示词索引
CHANGELOG.md            # 更新记录
CONTRIBUTING.md         # 贡献和持续迭代规则

Use this layout like a small content system. CATALOG.md is navigation. Prompt directories are source. Templates guide new prompts. Maintenance files and scripts protect consistency.

Step 4: Keep prompt metadata intact

The project defines prompt-file metadata shape. Preserve it when adapting files internally because it makes provenance and review possible.

title: 提示词标题
category: 一级分类
subcategory: 子类
source_section: 原合集章节号
author: 作者或来源
version: 提示词版本
created: 创建日期
status: active | draft | third-party-review
tags: 标签列表

Metadata is not cosmetic. In prompt operations, you need to know whether a prompt is active, draft, or third-party review; who authored it; which category it belongs to; and whether a later version replaced it.

Step 5: Run maintenance commands only when publishing changes

Official maintenance notes list three Python commands.

python3 scripts/check_repo.py

python3 scripts/generate_catalog.py

python3 scripts/generate_webpage.py

Use check_repo.py before publishing prompt changes. Rebuild catalog or webpage only when source changes require regenerated outputs.

Deeper Analysis

yao-open-prompts is valuable because it treats prompting as content architecture. Many prompt repos are organized by “cool examples.” This repo’s category plus subcategory approach makes prompts more findable. It also separates Chinese and English collections, which prevents bilingual files from becoming hard to review.

The bigger point: prompt reuse works only after adaptation. A prompt written for a marketing task may encode assumptions about audience, product maturity, channel, compliance, and output length. If you paste it blindly into an AI tool, you inherit those assumptions. Strong workflow is: choose prompt, add source material, add success criteria, add constraints, run once, review failure, revise, then store your adapted version with date and context.

For runany.dev readers building AI workflows, use this repo as seed material for prompt versioning. If a prompt powers blog briefs, SEO audits, customer replies, classroom plans, or coding assistance, copy exact version into your own repository or prompt registry. Link back to upstream source and note local modifications. That gives you reproducibility when model output changes.

The maintenance scripts are another signal. Even if you never run them, their presence reveals project intent: prompts should be checked, cataloged, and published consistently. That mindset is closer to documentation engineering than casual prompt sharing.

Limitations are predictable. Prompts are templates, not guarantees. They cannot verify facts, enforce compliance, or make model output deterministic. They can also encode outdated platform assumptions. Evaluation still belongs to user.

Practical Evaluation Checklist

Start from CATALOG.md, not random prompt files.
Prefer prompts with clear category, subcategory, status, version, and tags.
Keep Chinese and English variants separate in your own fork or workflow.
Add source material and constraints before running any prompt.
Save adapted prompts with commit hash or copy date.
Run python3 scripts/check_repo.py before contributing changes upstream.
Test important prompts across at least two model versions before operational use.

Security Notes

Prompt libraries can leak data if users paste sensitive source material into public chat tools. Before adapting prompts from yao-open-prompts, decide which model/provider can see your input. Remove secrets, customer data, private strategy, credentials, and unpublished financial information.

Also watch licensing and provenance for third-party reviewed prompts. If a prompt carries source metadata, keep attribution when moving it into internal docs. For automation, never let prompt output directly publish, email, or modify records without human review unless you have separate validation.

FAQ

Q: Do I need Python to use yao-open-prompts? A: No for normal use. Python appears for maintenance scripts such as repository checks and catalog/page generation.

Q: Where should I start? A: Start with CATALOG.md, choose category, then open matching prompt file under prompts/ or prompts-en/.

Q: Can I use English prompts? A: Yes. English prompts live under prompts-en/ and are kept separate from Chinese source prompts.

Q: Are prompts ready for production? A: Treat them as starting points. Add domain context, constraints, review rules, and output validation.

Q: What maintenance command should contributors run first? A: Run python3 scripts/check_repo.py before publishing changes.

Conclusion

yao-open-prompts is best understood as a maintained prompt knowledge base. Its catalog, bilingual separation, metadata convention, and maintenance scripts make it more useful than a loose snippet dump. Use it to bootstrap prompt design, but keep evaluation, privacy, and version control in your own workflow.