REPOGEO REPORT · LITE
pipiku915/FinMem-LLM-StockTrading
Default branch main · commit be814aa4 · scanned 5/30/2026, 9:03:12 AM
GitHub: 900 stars · 191 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 pipiku915/FinMem-LLM-StockTrading, 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 specific topics for better categorization
Why:
COPY-PASTE FIXllm, stock-trading, algorithmic-trading, finance, ai-agent, memory-networks, large-language-models
- highreadme#2Reposition README's opening to emphasize its function as an LLM trading agent
Why:
CURRENT# FINMEM: A Performance-Enhanced LLM Trading Agent with Layered Memory and Character Design [](https://www.python.org/downloads/release/python-3100/) [](https://opensource.org/licenses/MIT) [](https://github.com/ambv/black) [](https://arxiv.org/abs/2311.13743) ```text "So we beat on, boats against the current, borne back ceaselessly into the past." -- F. Scott Fitzgerald: The Great Gatsby ``` This repo provides the Python source code for the paper: FINMEM: A Performance-Enhanced Large Language Model Trading Agent with Layered Memory and Character Design [[PDF]](https://arxiv.org/pdf/2311.13743.pdf)COPY-PASTE FIX# FINMEM: A Performance-Enhanced LLM Trading Agent with Layered Memory and Character Design [](https://www.python.org/downloads/release/python-3100/) [](https://opensource.org/licenses/MIT) [](https://github.com/ambv/black) [](https://arxiv.org/abs/2311.13743) ```text "So we beat on, boats against the current, borne back ceaselessly into the past." -- F. Scott Fitzgerald: The Great Gatsby ``` This repository provides the Python source code for FinMem, an advanced LLM-powered stock trading agent. It implements layered memory and character design to enhance trading performance, as detailed in our paper: FINMEM: A Performance-Enhanced Large Language Model Trading Agent with Layered Memory and Character Design [[PDF]](https://arxiv.org/pdf/2311.13743.pdf) - mediumhomepage#3Add the arXiv paper link as the repository homepage
Why:
COPY-PASTE FIXhttps://arxiv.org/abs/2311.13743
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.
- GPT-4 · recommended 1×
- Claude 3 Opus · recommended 1×
- Llama 3 · recommended 1×
- Mixtral 8x7B · recommended 1×
- BloombergGPT · recommended 1×
- CATEGORY QUERYHow to build an intelligent stock trading agent using large language models?you: not recommendedAI recommended (in order):
- GPT-4
- Claude 3 Opus
- Llama 3
- Mixtral 8x7B
- BloombergGPT
- Google Gemini
- FinBERT
AI recommended 7 alternatives but never named pipiku915/FinMem-LLM-StockTrading. This is the gap to close.
Show full AI answer
- CATEGORY QUERYSeeking enhanced LLM solutions for algorithmic stock trading with advanced memory features.you: not recommendedAI recommended (in order):
- LangChain (langchain-ai/langchain)
- Redis (redis/redis)
- ChromaDB (chroma-core/chroma)
- LlamaIndex (run-llama/llama_index)
- Pinecone
- Weaviate (weaviate/weaviate)
- Haystack (deepset-ai/haystack)
- Elasticsearch (elastic/elasticsearch)
- Milvus (milvus-io/milvus)
- FAISS (facebookresearch/faiss)
- Annoy (spotify/annoy)
- Microsoft Semantic Kernel (microsoft/semantic-kernel)
- Azure Cosmos DB
AI recommended 13 alternatives but never named pipiku915/FinMem-LLM-StockTrading. This is the gap to close.
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 pipiku915/FinMem-LLM-StockTrading?passAI did not name pipiku915/FinMem-LLM-StockTrading — 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 pipiku915/FinMem-LLM-StockTrading in production, what risks or prerequisites should they evaluate first?passAI named pipiku915/FinMem-LLM-StockTrading 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 pipiku915/FinMem-LLM-StockTrading solve, and who is the primary audience?passAI did not name pipiku915/FinMem-LLM-StockTrading — 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 pipiku915/FinMem-LLM-StockTrading. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.
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pipiku915/FinMem-LLM-StockTrading — 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