RRepoGEO

REPOGEO REPORT · LITE

WillowHe/EvoOpt_oppangu_optimization_model

Default branch main · commit 6dd4a83d · scanned 6/17/2026, 3:18:24 PM

GitHub: 404 stars · 2 forks

AI VISIBILITY SCORE
22 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 1 warn · 0 fail
Objective metadata checks
AI knows your name
1 / 3
Direct prompts that named your repo
HOW TO READ THIS REPORT

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 WillowHe/EvoOpt_oppangu_optimization_model, 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.

OVERALL DIRECTION
  • highreadme#1
    Clarify 'oppangu' in README overview

    Why:

    CURRENT
    EvoOpt-LLM provides a comprehensive suite of solutions for fine-tuning and applying Large Language Models (LLMs) to operations research (OR) optimization tasks, using Openpangu-7B as the base model.
    COPY-PASTE FIX
    EvoOpt-LLM provides a comprehensive suite of solutions for fine-tuning and applying Large Language Models (LLMs) to operations research (OR) optimization tasks, leveraging the Openpangu-7B model. The 'oppangu' in the repository name specifically refers to this base model.
  • hightopics#2
    Add descriptive topics

    Why:

    CURRENT
    (none)
    COPY-PASTE FIX
    llm, operations-research, optimization, fine-tuning, openpangu, mathematical-modeling, constraint-generation, variable-pruning
  • mediumhomepage#3
    Add a homepage URL

    Why:

    CURRENT
    (none)
    COPY-PASTE FIX
    https://ai.gitcode.com/ascend-tribe/openpangu-embedded-7b-model/tree/main

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.

Recall
0 / 2
0% of queries surface WillowHe/EvoOpt_oppangu_optimization_model
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Wolfram Alpha
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Wolfram Alpha · recommended 2×
  2. OpenAI GPT-4 · recommended 1×
  3. GPT-3.5 · recommended 1×
  4. AMPL · recommended 1×
  5. Gurobi Python API · recommended 1×
  • CATEGORY QUERY
    How can I use large language models for operations research optimization tasks?
    you: not recommended
    AI recommended (in order):
    1. OpenAI GPT-4
    2. GPT-3.5
    3. AMPL
    4. Gurobi Python API
    5. PuLP
    6. Pyomo
    7. GurobiPy
    8. OR-Tools
    9. Google Gemini
    10. Microsoft Copilot
    11. GitHub Copilot
    12. Hugging Face Transformers
    13. Llama 2
    14. Mistral
    15. T5
    16. LangChain
    17. LlamaIndex
    18. Gurobi
    19. CPLEX
    20. Wolfram Alpha

    AI recommended 20 alternatives but never named WillowHe/EvoOpt_oppangu_optimization_model. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What tools help generate mathematical models from natural language descriptions?
    you: not recommended
    AI recommended (in order):
    1. ChatGPT / GPT-4
    2. Claude
    3. Bard
    4. Wolfram Alpha
    5. Wolfram Language
    6. SymPy (sympy/sympy)
    7. OpenCog (opencog/opencog)
    8. AtomSpace
    9. Neo4j (neo4j/neo4j)
    10. OWL
    11. Pellet
    12. HermiT

    AI recommended 12 alternatives but never named WillowHe/EvoOpt_oppangu_optimization_model. This is the gap to close.

    Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

  • Metadata completeness
    warn

    Suggestion:

  • README presence
    pass

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 WillowHe/EvoOpt_oppangu_optimization_model?
    pass
    AI did not name WillowHe/EvoOpt_oppangu_optimization_model — 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 WillowHe/EvoOpt_oppangu_optimization_model in production, what risks or prerequisites should they evaluate first?
    pass
    AI named WillowHe/EvoOpt_oppangu_optimization_model 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 WillowHe/EvoOpt_oppangu_optimization_model solve, and who is the primary audience?
    pass
    AI did not name WillowHe/EvoOpt_oppangu_optimization_model — 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

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WillowHe/EvoOpt_oppangu_optimization_model — 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