REPOGEO REPORT · LITE
SCIR-TG/FengZhengLLM
Default branch main · commit 5c561322 · scanned 6/3/2026, 3:38:07 AM
GitHub: 517 stars · 1 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 SCIR-TG/FengZhengLLM, 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.
- highabout#1Add a concise repository description
Why:
COPY-PASTE FIXFengZhengLLM: A specialized Chinese Large Language Model for aerospace knowledge, developed by HIT-SCIR-TG.
- hightopics#2Add relevant topics to the repository
Why:
COPY-PASTE FIX["llm", "large-language-model", "aerospace", "astronautics", "space-science", "chinese-llm", "knowledge-base", "question-answering", "hit-scir"]
- mediumhomepage#3Add the online experience link as the repository homepage
Why:
COPY-PASTE FIXAdd the '模型在线体验链接' (Model online experience link) mentioned in the README to the repository's homepage field.
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.
- Llama 3 · recommended 1×
- Mistral 7B · recommended 1×
- Mixtral 8x7B · recommended 1×
- Gemma · recommended 1×
- Falcon · recommended 1×
- CATEGORY QUERYWhat open-source large language models are available for deep space exploration knowledge?you: not recommendedAI recommended (in order):
- Llama 3
- Mistral 7B
- Mixtral 8x7B
- Gemma
- Falcon
- MPT-7B
- MPT-30B
AI recommended 7 alternatives but never named SCIR-TG/FengZhengLLM. This is the gap to close.
Show full AI answer
- CATEGORY QUERYHow can I develop an AI-powered question answering system focused on astronautics and space science?you: not recommendedAI recommended (in order):
- Hugging Face Transformers
- Elasticsearch
- FAISS
- SpaCy
- Streamlit
- Scikit-learn
- PyTorch
AI recommended 7 alternatives but never named SCIR-TG/FengZhengLLM. This is the gap to close.
Show full AI answer
Objective checks
Rule-based audits of metadata signals AI engines weight most.
- Metadata completenessfail
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 SCIR-TG/FengZhengLLM?passAI did not name SCIR-TG/FengZhengLLM — 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?
- If a team adopts SCIR-TG/FengZhengLLM in production, what risks or prerequisites should they evaluate first?passAI named SCIR-TG/FengZhengLLM 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 SCIR-TG/FengZhengLLM solve, and who is the primary audience?passAI named SCIR-TG/FengZhengLLM explicitly
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 SCIR-TG/FengZhengLLM. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.
[](https://repogeo.com/en/r/SCIR-TG/FengZhengLLM)<a href="https://repogeo.com/en/r/SCIR-TG/FengZhengLLM"><img src="https://repogeo.com/badge/SCIR-TG/FengZhengLLM.svg" alt="RepoGEO" /></a>Subscribe to Pro for deep diagnoses
SCIR-TG/FengZhengLLM — 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