RRepoGEO

REPOGEO REPORT · LITE

chorus-codes/chorus

Default branch main · commit a0921707 · scanned 6/11/2026, 5:22:09 PM

GitHub: 518 stars · 55 forks

AI VISIBILITY SCORE
40 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
2 pass · 0 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 chorus-codes/chorus, 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 specific, application-oriented topics

    Why:

    CURRENT
    claude-code, codex, llm
    COPY-PASTE FIX
    ai-code-review, llm-peer-review, multi-llm, code-quality, generative-ai, cost-effective-ai, chatgpt-pro, claude-pro, gemini-advanced
  • highabout#2
    Refine the 'About' description for explicit clarity

    Why:

    CURRENT
    Multi-LLM peer review for code decisions. Bring your own CLI; Chorus convenes 2-4 other LLMs to review the work before you ship.
    COPY-PASTE FIX
    An AI code review tool for multi-LLM peer review of AI-generated code. Chorus convenes 2-4 LLMs (using your existing subscriptions) to review code decisions before you ship, ensuring quality and catching AI blind spots.
  • mediumreadme#3
    Add a 'How Chorus is Different' section to the README

    Why:

    COPY-PASTE FIX
    ### How Chorus is Different (vs. LLM Frameworks & Models)
Chorus is not an LLM framework like LangChain or LlamaIndex, nor is it an LLM model like Code Llama. Instead, Chorus is a specialized application designed to perform multi-LLM peer review of AI-generated code. It leverages your existing AI subscriptions (ChatGPT Plus, Claude Pro, Gemini Advanced) to provide diverse, cost-effective code quality checks, rather than providing APIs for building new LLM applications or serving models.

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 chorus-codes/chorus
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
LangChain
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. LangChain · recommended 1×
  2. LlamaIndex · recommended 1×
  3. OpenAI API · recommended 1×
  4. Microsoft Semantic Kernel · recommended 1×
  5. Hugging Face Transformers · recommended 1×
  • CATEGORY QUERY
    Need a way to have multiple LLMs review AI-generated code for errors.
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. LlamaIndex
    3. OpenAI API
    4. Microsoft Semantic Kernel
    5. Hugging Face Transformers
    6. Guardrails AI

    AI recommended 6 alternatives but never named chorus-codes/chorus. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    How to get diverse AI code reviews without incurring high API costs?
    you: not recommended
    AI recommended (in order):
    1. Code Llama
    2. Mistral 7B Instruct
    3. Hugging Face Transformers (huggingface/transformers)
    4. Ollama (ollama/ollama)
    5. DeepSeek Coder
    6. Llama 2

    AI recommended 6 alternatives but never named chorus-codes/chorus. This is the gap to close.

    Show full AI answer

Objective checks

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

  • Metadata completeness
    pass

  • 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 chorus-codes/chorus?
    pass
    AI named chorus-codes/chorus explicitly

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

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

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

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chorus-codes/chorus — 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