How sogoojoy/awesome-chatgpt-prompts-zh works
1. Repository type
- This is a documentation/content repository, not an application or service.
- Its primary artifact is a large Markdown prompt catalog for ChatGPT usage in Chinese.
2. Core purpose
- The repo collects “prompt engineering” examples and role-play templates.
- Users copy a prompt from README.md into ChatGPT (or a similar LLM) to steer responses.
3. Main content surface
- README.md is the main entry point and effectively the product UI.
- It contains:
- project introduction
- examples of how to use prompts
- a long list of prompt templates by role/task
- links to the upstream repo and mirrors
4. Usage guidance
- USEAGE.md is a supporting document with examples and walkthrough-style content.
- The README points to it for “picture examples” and more usage cases.
- This makes the repo a two-layer content system: overview in README, examples in USEAGE.
5. Prompt library subsystem
- The largest subsystem is the prompt library, organized as sections such as:
- translation/improvement
- frontend helper
- interviewer/interviewee
- terminal/console emulation
- writing, debating, coaching, analysis, and many other role prompts
- These are mostly self-contained text templates that can be reused as-is.
6. Interaction model / data flow
- The flow is simple:
1. user reads a prompt in the repo
2. copies it into ChatGPT as input
3. ChatGPT generates a response according to the template
- There is no internal execution pipeline; the LLM is the runtime boundary outside the repo.
7. Media assets
- pic/ stores screenshots or illustrative images referenced by the README/usage docs.
- These assets support the documentation and show expected prompt behavior or example outputs.
8. External dependencies and boundaries
- The repo depends conceptually on:
- OpenAI ChatGPT as the execution target
- GitHub/Gitee as distribution mirrors
- No code-level dependency graph exists; the architectural boundary is between static prompt content and external AI service.
9. Operational characteristics
- There is no backend, database, API, or build system.
- Maintenance is editorial: adding, editing, or translating prompt templates and examples.
10. Content structure pattern
- Most prompt entries follow a repetitive pattern:
- “I want you to act as…”
- task constraints
- output format constraints
- a sample first request
- This consistent pattern is the repo’s main organizational mechanism.
11. Important implication for diagrams
- If drawing an architecture diagram, model this repo as:
- a static content repository at the center
- markdown docs and images as stored assets
- an external LLM consumer/execution target
- users as the primary actors copying content out of the repo
12. Overall summary
- Architecturally, this is a prompt knowledge base rather than software infrastructure.
- The key “system behavior” happens when humans apply the stored prompts to ChatGPT; the repository itself is just the packaged source of those instructions.
Main entry points: README.md README · USEAGE.md Usage guide · pic Screenshots
Components 9
Markdown docs
Primary content surface and usage guidance.
- README · Main entry point and prompt catalog surface.
README.md - Usage guide · Supporting examples and usage walkthroughs.
USEAGE.md - Prompt library · Reusable role-play and task prompts organized by section.
- Examples · Sample interactions showing how prompts behave in practice.
- Prompt sections · Translation, frontend, interview, writing, debating, coaching, and other prompt categories.
Media assets
Illustrative screenshots referenced by the docs.
- Screenshots · Illustrative images used by the docs.
pic
External boundary
Humans and the LLM service outside the repository.
- Reader · Copies prompts from the repo into an LLM chat.
- ChatGPT · External model that executes the pasted prompts.
- Mirrors · References to upstream and mirrored hosting locations.
Connections 10
- Reader → README: reads prompts · Primary consumption path from the catalog entry point to the human.
- README → Prompt library: contains · README is the main container for the prompt catalog.
- Prompt library → Prompt sections: organized as · The catalog is split into repeated role/task sections.
- README → Usage guide: points to · README directs readers to the usage walkthroughs.
- Usage guide → Examples: shows · Usage guide provides concrete examples and walkthroughs.
- README → Screenshots: references · Screenshots and illustrations support the docs.
- Reader → ChatGPT: pastes prompt · The human copies a prompt into the external LLM boundary.
- ChatGPT → Reader: responds · The model generates the requested output.
- README → Mirrors: links to · README includes upstream and mirror references.
- Usage guide → Screenshots: illustrates · Usage content is supported by images in pic/.