RRepoGEO

REPOGEO REPORT · LITE

bigcode-project/starcoder

Default branch main · commit d72c7fe3 · scanned 6/25/2026, 10:08:00 AM

GitHub: 7,508 stars · 527 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)

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

AI VISIBILITY SCORE
63 /100
Needs work
Category recall
1 / 2
Avg rank #3.0 when recommended
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

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

OVERALL DIRECTION
  • hightopics#1
    Add relevant topics to improve categorization

    Why:

    COPY-PASTE FIX
    large-language-model, code-generation, llm, finetuning, code-llm, programming-languages, machine-learning, deep-learning, nlp
  • highreadme#2
    Reposition the README H1 to emphasize multi-language code generation

    Why:

    CURRENT
    # What is this about?
💫 StarCoder is a language model (LM) trained on source code and natural language text. Its training data incorporates more that 80 different programming languages as well as text extracted from GitHub issues and commits and from notebooks. This repository showcases how we get an overview of this LM's capabilities.
    COPY-PASTE FIX
    # 💫 StarCoder: A Large Language Model for Code Generation Across 80+ Programming Languages

This repository is the home of StarCoder, a powerful language model (LM) specifically trained on a vast dataset of source code and natural language text. With support for over 80 different programming languages, StarCoder excels at code generation, completion, and understanding, making it ideal for developers and researchers.
  • mediumhomepage#3
    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
1 / 2
50% of queries surface bigcode-project/starcoder
Avg rank
#3.0
Lower is better. #1 = top recommendation.
Share of voice
8%
Of all named tools, what % are you?
Top rival
Google Gemini
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Google Gemini · recommended 2×
  2. GitHub Copilot · recommended 1×
  3. OpenAI GPT-4 · recommended 1×
  4. GPT-3.5 Turbo · recommended 1×
  5. Meta Code Llama · recommended 1×
  • CATEGORY QUERY
    Which large language models are effective for generating code across multiple programming languages?
    you: not recommended
    AI recommended (in order):
    1. GitHub Copilot
    2. Google Gemini
    3. OpenAI GPT-4
    4. GPT-3.5 Turbo
    5. Meta Code Llama
    6. Anthropic Claude 3
    7. Amazon CodeWhisperer

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

    Show full AI answer
  • CATEGORY QUERY
    How can I fine-tune a language model to act as a helpful coding assistant?
    you: #3
    AI recommended (in order):
    1. OpenAI GPT-3.5 Turbo / GPT-4
    2. Code Llama
    3. StarCoder / StarCoder2 (bigcode-project/starcoder) ← you
    4. DeepSeek-Coder
    5. Google Gemini
    6. Mistral Large / Mixtral 8x7B
    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?

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bigcode-project/starcoder — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

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  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite