RRepoGEO

REPOGEO REPORT · LITE

OpenBioLink/ThoughtSource

Default branch main · commit 760b2c7f · scanned 5/21/2026, 3:56:50 AM

GitHub: 1,015 stars · 81 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
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 OpenBioLink/ThoughtSource, 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
    Clarify the README's opening statement to emphasize chain-of-thought data and tools

    Why:

    CURRENT
    __A framework for the science of machine thinking__
    COPY-PASTE FIX
    __A central, open resource for chain-of-thought reasoning data and tools in large language models__
  • highhomepage#2
    Add the project homepage URL

    Why:

    COPY-PASTE FIX
    https://samwald.info/
  • mediumtopics#3
    Add specific chain-of-thought and LLM-related topics

    Why:

    CURRENT
    dataset, machine-learning, natural-language-processing, question-answering, reasoning
    COPY-PASTE FIX
    dataset, machine-learning, natural-language-processing, question-answering, reasoning, chain-of-thought, llm, large-language-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 OpenBioLink/ThoughtSource
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. LlamaIndex · recommended 2×
  3. Hugging Face Transformers Library · recommended 1×
  4. OpenAI API · recommended 1×
  5. Anthropic API · recommended 1×
  • CATEGORY QUERY
    Where can I find datasets and tools to improve chain-of-thought reasoning in large language models?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. LlamaIndex
    3. Hugging Face Transformers Library
    4. OpenAI API
    5. Anthropic API
    6. Google Gemini API
    7. AutoGPT
    8. BabyAGI

    AI recommended 8 alternatives but never named OpenBioLink/ThoughtSource. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What frameworks help manage and process chain-of-thought reasoning datasets for LLM training?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. LlamaIndex
    3. PromptFlow
    4. Haystack
    5. DSPy
    6. Guidance
    7. Outlines

    AI recommended 7 alternatives but never named OpenBioLink/ThoughtSource. 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 OpenBioLink/ThoughtSource?
    pass
    AI named OpenBioLink/ThoughtSource explicitly

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

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

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

Embed your GEO score

Drop this badge into the README of OpenBioLink/ThoughtSource. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

RepoGEO badge previewLive preview
MARKDOWN (README)
[![RepoGEO](https://repogeo.com/badge/OpenBioLink/ThoughtSource.svg)](https://repogeo.com/en/r/OpenBioLink/ThoughtSource)
HTML
<a href="https://repogeo.com/en/r/OpenBioLink/ThoughtSource"><img src="https://repogeo.com/badge/OpenBioLink/ThoughtSource.svg" alt="RepoGEO" /></a>
Pro

Subscribe to Pro for deep diagnoses

OpenBioLink/ThoughtSource — 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