REPOGEO REPORT · LITE
PandaBearLab/prompt-tutorial
Default branch main · commit 6ccf4c87 · scanned 5/25/2026, 12:32:56 PM
GitHub: 1,329 stars · 111 forks
Action plan is what to do next — copy-pasteable changes prioritized by impact. Category visibility is the real GEO test: when a user asks an AI a brand-free question that should surface PandaBearLab/prompt-tutorial, does the AI actually recommend you — or your competitors? Objective checks verify the metadata signals AI engines weight first. Self-mention check detects whether AI even knows you exist by name.
Action plan — copy-paste fixes
3 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.
- hightopics#1Add relevant English topics to the repository
Why:
COPY-PASTE FIXprompt-engineering, llm, large-language-models, chatgpt, tutorial, prompt-design, ai-prompts, nlp, machine-learning
- highlicense#2Add a LICENSE file to the repository
Why:
COPY-PASTE FIX(Create a LICENSE file in the repository root with a standard open-source license like MIT or Apache-2.0.)
- mediumreadme#3Add a concise English summary at the very top of the README
Why:
CURRENTtitle: 我的大语言模型课
COPY-PASTE FIXThis repository offers a comprehensive, practical tutorial on prompt engineering for Large Language Models (LLMs) such as ChatGPT. It covers best practices for crafting effective prompts for tasks like text summarization, inference, content generation, and building chatbots.
Category GEO backends resolved for this scan: google/gemini-2.5-flash, deepseek/deepseek-v4-flash
Category visibility — the real GEO test
Brand-free queries asked to google/gemini-2.5-flash. Did AI recommend you, or someone else?
Same questions for every model — switch tabs to compare answers and rankings.
- CATEGORY QUERYWhat are best practices for crafting effective prompts to improve large language model performance?you: not recommended
Show full AI answer
- CATEGORY QUERYHow to design prompts for LLMs to handle text summarization, inference, and translation tasks?you: not recommended
Show full AI answer
Objective checks
Rule-based audits of metadata signals AI engines weight most.
- Metadata completenesswarn
Suggestion:
- README presencepass
Self-mention check
Does AI even know your repo exists when asked about it directly?
- Compared to common alternatives in this category, what is the core differentiator of PandaBearLab/prompt-tutorial?passAI named PandaBearLab/prompt-tutorial explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
- If a team adopts PandaBearLab/prompt-tutorial in production, what risks or prerequisites should they evaluate first?passAI named PandaBearLab/prompt-tutorial explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
- In one sentence, what problem does the repo PandaBearLab/prompt-tutorial solve, and who is the primary audience?passAI did not name PandaBearLab/prompt-tutorial — likely talking about a different project
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
Embed your GEO score
Drop this badge into the README of PandaBearLab/prompt-tutorial. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.
Live preview[](https://repogeo.com/en/r/PandaBearLab/prompt-tutorial)<a href="https://repogeo.com/en/r/PandaBearLab/prompt-tutorial"><img src="https://repogeo.com/badge/PandaBearLab/prompt-tutorial.svg" alt="RepoGEO" /></a>Subscribe to Pro for deep diagnoses
PandaBearLab/prompt-tutorial — Lite scans stay free; this card itemizes Pro deep limits vs Lite.
- Deep reports10 / month
- Brand-free category queries5 vs 2 in Lite
- Prioritized action items8 vs 3 in Lite