RRepoGEO

REPOGEO REPORT · LITE

alvinreal/awesome-autoresearch

Default branch main · commit b99fab17 · scanned 6/24/2026, 1:18:24 AM

GitHub: 2,262 stars · 171 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
33 /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
2 / 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 alvinreal/awesome-autoresearch, 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
    Reposition README opening to clarify 'awesome list' nature

    Why:

    CURRENT
    **A curated, high-signal index of autonomous improvement loops, research agents, and descendants inspired bykarpathy/autoresearch**.
    COPY-PASTE FIX
    **A curated, high-signal index of autonomous improvement loops, research agents, and descendants inspired bykarpathy/autoresearch. This is a resource for discovering projects and tools, not an implementation framework or library itself.**
  • mediumlicense#2
    Clarify license details in README

    Why:

    COPY-PASTE FIX
    Add the following sentence to the 'License' section of your README: 'This project is licensed under [SPECIFIC LICENSE NAME(S) HERE]. Please see the [LICENSE](LICENSE) file for full terms.'
  • lowreadme#3
    Add a section differentiating from implementation frameworks

    Why:

    COPY-PASTE FIX
    Add a new section to the README titled 'Why an Awesome List, Not a Framework?' or 'How is this different from LangChain/AutoGPT?'. In this section, explain that this repository is a curated index for discovery, not an implementation library or framework, and that it complements such tools by helping users find them.

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 alvinreal/awesome-autoresearch
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
LangChain
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. LangChain · recommended 2×
  2. OpenAI API · recommended 2×
  3. Hugging Face Transformers · recommended 2×
  4. AutoGPT / BabyAGI · recommended 1×
  5. DeepMind's Acme · recommended 1×
  • CATEGORY QUERY
    How to implement autonomous AI agents that continuously learn and improve themselves?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. AutoGPT / BabyAGI
    3. OpenAI API
    4. DeepMind's Acme
    5. Ray RLlib
    6. Hugging Face Transformers
    7. TensorFlow / PyTorch

    AI recommended 7 alternatives but never named alvinreal/awesome-autoresearch. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking a comprehensive list of tools for building self-improving research agents.
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. LlamaIndex
    3. AutoGPT
    4. BabyAGI
    5. OpenAI API
    6. Anthropic API
    7. Google Gemini API
    8. Faiss
    9. Pinecone
    10. Weaviate
    11. Hugging Face Transformers
    12. Hugging Face Datasets
    13. Docker
    14. Kubernetes

    AI recommended 14 alternatives but never named alvinreal/awesome-autoresearch. 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 alvinreal/awesome-autoresearch?
    pass
    AI did not name alvinreal/awesome-autoresearch — 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 alvinreal/awesome-autoresearch in production, what risks or prerequisites should they evaluate first?
    pass
    AI named alvinreal/awesome-autoresearch 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 alvinreal/awesome-autoresearch solve, and who is the primary audience?
    pass
    AI named alvinreal/awesome-autoresearch explicitly

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

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alvinreal/awesome-autoresearch — 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