RRepoGEO

REPOGEO REPORT · LITE

open-tinker/OpenTinker

Default branch main · commit f87fe25f · scanned 6/11/2026, 1:57:54 PM

GitHub: 675 stars · 63 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 open-tinker/OpenTinker, 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 the repository

    Why:

    COPY-PASTE FIX
    reinforcement-learning, llm, foundation-models, agentic-ai, rlas, machine-learning, deep-learning, ai-agents
  • highreadme#2
    Add a clear H1 title to the README

    Why:

    COPY-PASTE FIX
    # OpenTinker: RL-as-a-Service Infrastructure for Foundation Models

Democratizing Agentic Reinforcement Learning as a Service
  • mediumhomepage#3
    Add the project homepage URL to the repository's About section

    Why:

    COPY-PASTE FIX
    https://open-tinker.github.io/opentinker-page/

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 open-tinker/OpenTinker
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
ray-project/ray
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. ray-project/ray · recommended 2×
  2. tensorflow/tensorflow · recommended 1×
  3. pytorch/pytorch · recommended 1×
  4. huggingface/transformers · recommended 1×
  5. huggingface/trl · recommended 1×
  • CATEGORY QUERY
    What are the best platforms for applying reinforcement learning to foundation models?
    you: not recommended
    AI recommended (in order):
    1. Ray RLlib (ray-project/ray)
    2. Ray (ray-project/ray)
    3. TensorFlow (tensorflow/tensorflow)
    4. PyTorch (pytorch/pytorch)
    5. Hugging Face Transformers (huggingface/transformers)
    6. trl (huggingface/trl)
    7. PEFT (huggingface/peft)
    8. DeepMind Acme (deepmind/acme)
    9. OpenAI Baselines (openai/baselines)
    10. Stable Baselines3 (DLR-RM/stable-baselines3)
    11. TensorFlow Agents (TF-Agents) (tensorflow/agents)
    12. PyTorch Lightning (Lightning-AI/lightning)

    AI recommended 12 alternatives but never named open-tinker/OpenTinker. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    How can I build and deploy agentic reinforcement learning systems for LLM tasks?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. Stable Baselines3
    3. RLlib
    4. LlamaIndex
    5. PyTorch
    6. TensorFlow
    7. Hugging Face Transformers Agents
    8. TRL (Transformer Reinforcement Learning)
    9. Gymnasium
    10. Microsoft Guidance

    AI recommended 10 alternatives but never named open-tinker/OpenTinker. 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 open-tinker/OpenTinker?
    pass
    AI named open-tinker/OpenTinker explicitly

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

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

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

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open-tinker/OpenTinker — 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