RRepoGEO

REPOGEO REPORT · LITE

sahil280114/codealpaca

Default branch master · commit 2f78ddc5 · scanned 6/30/2026, 7:28:18 PM

GitHub: 1,512 stars · 112 forks

Scan history for this repo

Score trend below includes all ready runs (older left, newer right; scroll horizontally if needed). The table is collapsed by default—expand for newest-first rows, 10 per page.

Score trend (left → right: older → newer)

2 ready scans. Expand the table below for newest-first rows (10 per page, paginated).

AI VISIBILITY SCORE
30 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 0 warn · 1 fail
Objective metadata checks
AI knows your name
3 / 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 sahil280114/codealpaca, 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
  • highabout#1
    Add a concise repository description

    Why:

    COPY-PASTE FIX
    An instruction-following LLaMA model fine-tuned on code generation instructions, along with its dataset and training code.
  • hightopics#2
    Add relevant topics to the repository

    Why:

    COPY-PASTE FIX
    llama, code-generation, instruction-following, fine-tuning, large-language-models, llm, dataset, self-instruct
  • mediumhomepage#3
    Add the demo URL as the repository homepage

    Why:

    COPY-PASTE FIX
    https://code-alpaca-demo.vercel.app/

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 sahil280114/codealpaca
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Code Llama
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Code Llama · recommended 2×
  2. OpenAI GPT-3.5/GPT-4 Fine-tuning API · recommended 1×
  3. huggingface/transformers · recommended 1×
  4. Llama 2 · recommended 1×
  5. StarCoder · recommended 1×
  • CATEGORY QUERY
    How can I train a custom code generation AI using existing foundation models?
    you: not recommended
    AI recommended (in order):
    1. OpenAI GPT-3.5/GPT-4 Fine-tuning API
    2. Hugging Face Transformers (huggingface/transformers)
    3. Llama 2
    4. Code Llama
    5. StarCoder
    6. DeepSpeed (microsoft/DeepSpeed)
    7. Accelerate (huggingface/accelerate)
    8. Google Cloud Vertex AI
    9. Codey
    10. PaLM 2
    11. OpenAI GPT-4
    12. OpenAI GPT-3.5 Turbo
    13. Anthropic Claude 2
    14. Google Gemini Pro
    15. Google Gemini Ultra
    16. LangChain (langchain-ai/langchain)
    17. LlamaIndex (run-llama/llama_index)
    18. Faiss (facebookresearch/faiss)
    19. Pinecone
    20. Weaviate (weaviate/weaviate)

    AI recommended 20 alternatives but never named sahil280114/codealpaca. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Looking for open-source instruction-following models to assist with programming tasks.
    you: not recommended
    AI recommended (in order):
    1. Code Llama
    2. DeepSeek Coder
    3. WizardCoder
    4. StarCoder2
    5. Phind-CodeLlama
    6. Mistral-7B-Instruct-v0.2

    AI recommended 6 alternatives but never named sahil280114/codealpaca. This is the gap to close.

    Show full AI answer

Objective checks

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

  • Metadata completeness
    fail

    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 sahil280114/codealpaca?
    pass
    AI named sahil280114/codealpaca explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • If a team adopts sahil280114/codealpaca in production, what risks or prerequisites should they evaluate first?
    pass
    AI named sahil280114/codealpaca 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 sahil280114/codealpaca solve, and who is the primary audience?
    pass
    AI named sahil280114/codealpaca explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

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sahil280114/codealpaca — 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