RRepoGEO

REPOGEO REPORT · LITE

bigcode-project/starcoder

Default branch main · commit d72c7fe3 · scanned 5/14/2026, 8:28:15 PM

GitHub: 7,512 stars · 531 forks

AI VISIBILITY SCORE
35 /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
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 bigcode-project/starcoder, 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

2 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION
  • highreadme#1
    Reposition the README's core purpose for AI in the opening sentence

    Why:

    CURRENT
    💫 StarCoder is a language model (LM) trained on source code and natural language text.
    COPY-PASTE FIX
    💫 StarCoder is a powerful large language model (LLM) designed for **code generation**, **code completion**, and **programming assistance**, trained on a vast dataset of source code and natural language.
  • mediumhomepage#2
    Add a homepage URL to the repository metadata

    Why:

    COPY-PASTE FIX
    https://huggingface.co/bigcode/starcoder

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 bigcode-project/starcoder
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
OpenAI Codex
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. OpenAI Codex · recommended 1×
  2. GitHub Copilot · recommended 1×
  3. Google Gemini · recommended 1×
  4. Anthropic Claude · recommended 1×
  5. Meta Code Llama · recommended 1×
  • CATEGORY QUERY
    What AI models can generate code snippets from natural language descriptions?
    you: not recommended
    AI recommended (in order):
    1. OpenAI Codex
    2. GitHub Copilot
    3. Google Gemini
    4. Anthropic Claude
    5. Meta Code Llama
    6. Hugging Face CodeGen
    7. DeepMind AlphaCode

    AI recommended 7 alternatives but never named bigcode-project/starcoder. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    How to fine-tune a large language model for programming assistance and code completion?
    you: not recommended
    AI recommended (in order):
    1. Hugging Face Transformers
    2. CodeLlama
    3. DeepSeek Coder
    4. StarCoder2
    5. Mistral 7B
    6. transformers library (huggingface/transformers)
    7. PEFT (huggingface/peft)
    8. LoRA
    9. QLoRA
    10. datasets library (huggingface/datasets)
    11. PyTorch (pytorch/pytorch)
    12. TensorFlow (tensorflow/tensorflow)
    13. OpenAI Fine-tuning API
    14. gpt-3.5-turbo
    15. OpenAI API
    16. Google Cloud Vertex AI
    17. CodeGemma
    18. Gemini Pro
    19. Microsoft Azure Machine Learning
    20. Phi-3
    21. vLLM (vllm-project/vllm)
    22. Axolotl (OpenAccess-AI-Collective/axolotl)
    23. Lit-GPT (Lightning-AI/lit-gpt)

    AI recommended 23 alternatives but never named bigcode-project/starcoder. 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 bigcode-project/starcoder?
    pass
    AI named bigcode-project/starcoder explicitly

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

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

    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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bigcode-project/starcoder — 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