RRepoGEO

REPOGEO REPORT · LITE

thunlp/ToolLearningPapers

Default branch master · commit 0b5e6690 · scanned 6/3/2026, 8:27:18 PM

GitHub: 922 stars · 41 forks

AI VISIBILITY SCORE
17 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 0 warn · 1 fail
Objective metadata checks
AI knows your name
1 / 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 thunlp/ToolLearningPapers, 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
  • highabout#1
    Add a concise description to the About section

    Why:

    COPY-PASTE FIX
    A curated, must-read collection of research papers and resources on tool learning with large language models (LLMs) and foundation models.
  • hightopics#2
    Add relevant topics to the repository

    Why:

    COPY-PASTE FIX
    tool-learning, large-language-models, llms, foundation-models, ai-research, paper-list, research-papers, machine-learning, nlp
  • mediumreadme#3
    Refine README's opening to emphasize 'curated collection'

    Why:

    CURRENT
    Must-read papers on tool learning with foundation models.
    COPY-PASTE FIX
    A curated, must-read collection of research papers and resources on tool learning with large language models (LLMs) and foundation 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 thunlp/ToolLearningPapers
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
arXiv
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. arXiv · recommended 1×
  2. Google Scholar · recommended 1×
  3. ACL Anthology · recommended 1×
  4. Semantic Scholar · recommended 1×
  5. NeurIPS · recommended 1×
  • CATEGORY QUERY
    Where can I find research papers on large language models interacting with external tools?
    you: not recommended
    AI recommended (in order):
    1. arXiv
    2. Google Scholar
    3. ACL Anthology
    4. Semantic Scholar
    5. NeurIPS
    6. ICML
    7. ICLR
    8. EMNLP
    9. ACL
    10. Hugging Face
    11. GitHub

    AI recommended 11 alternatives but never named thunlp/ToolLearningPapers. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are the key challenges and benefits of integrating AI models with specialized tools?
    you: not recommended
    AI recommended (in order):
    1. FastAPI
    2. Flask
    3. Docker
    4. Podman
    5. Kubernetes
    6. Apache Kafka
    7. MLflow
    8. Airflow
    9. Prefect
    10. Zapier
    11. Make

    AI recommended 11 alternatives but never named thunlp/ToolLearningPapers. This is the gap to close.

    Show full AI answer

Objective checks

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

  • Metadata completeness
    fail

    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 thunlp/ToolLearningPapers?
    pass
    AI did not name thunlp/ToolLearningPapers — 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 thunlp/ToolLearningPapers in production, what risks or prerequisites should they evaluate first?
    pass
    AI named thunlp/ToolLearningPapers 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 thunlp/ToolLearningPapers solve, and who is the primary audience?
    pass
    AI did not name thunlp/ToolLearningPapers — 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?

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thunlp/ToolLearningPapers — 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