REPOGEO REPORT · LITE
WXY604/LLM-based-causal-discovery
Default branch main · commit bf2c2b77 · scanned 6/14/2026, 8:36:45 AM
GitHub: 837 stars · 61 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 WXY604/LLM-based-causal-discovery, 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 'About' description for the repository
Why:
COPY-PASTE FIXA toolkit for LLM-augmented causal discovery, enabling inference of causal relationships from observational data with reduced reliance on extensive domain expert knowledge.
- hightopics#2Add relevant topics to improve categorization and search
Why:
COPY-PASTE FIXcausal-discovery, llm, causal-inference, observational-data, machine-learning, artificial-intelligence, data-science
- highlicense#3Add a LICENSE file to clarify usage rights
Why:
COPY-PASTE FIXCreate a LICENSE file in the repository root, for example, by adding a standard MIT License or Apache-2.0 License.
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.
- DoWhy · recommended 2×
- EconML · recommended 2×
- TETRAD · recommended 2×
- Causal AI · recommended 1×
- WhyLabs · recommended 1×
- CATEGORY QUERYHow to leverage large language models for automated causal relationship discovery from data?you: not recommendedAI recommended (in order):
- Causal AI
- WhyLabs
- causaLens
- DoWhy
- EconML
- GPT-4
- Claude 3 Opus
- Neo4j
- GraphRAG
- TETRAD
- CausalNex
AI recommended 11 alternatives but never named WXY604/LLM-based-causal-discovery. This is the gap to close.
Show full AI answer
- CATEGORY QUERYWhat tools help infer causal links from observational data without extensive domain expert input?you: not recommendedAI recommended (in order):
- DoWhy
- CausalPy
- EconML
- DAGitty
- Tidymodels
- TETRAD
AI recommended 6 alternatives but never named WXY604/LLM-based-causal-discovery. 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 WXY604/LLM-based-causal-discovery?passAI did not name WXY604/LLM-based-causal-discovery — 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 WXY604/LLM-based-causal-discovery in production, what risks or prerequisites should they evaluate first?passAI did not name WXY604/LLM-based-causal-discovery — 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?
- In one sentence, what problem does the repo WXY604/LLM-based-causal-discovery solve, and who is the primary audience?passAI did not name WXY604/LLM-based-causal-discovery — 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 WXY604/LLM-based-causal-discovery. 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/WXY604/LLM-based-causal-discovery)<a href="https://repogeo.com/en/r/WXY604/LLM-based-causal-discovery"><img src="https://repogeo.com/badge/WXY604/LLM-based-causal-discovery.svg" alt="RepoGEO" /></a>Subscribe to Pro for deep diagnoses
WXY604/LLM-based-causal-discovery — 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