RRepoGEO

REPOGEO REPORT · LITE

qiancheng0/ToolRL

Default branch main · commit 8cee13ec · scanned 6/16/2026, 9:48:35 PM

GitHub: 503 stars · 36 forks

AI VISIBILITY SCORE
30 /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
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 qiancheng0/ToolRL, 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

2 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
    ToolRL is a research framework and benchmark for training large language models to use tools via reinforcement learning, based on the paper 'ToolRL: Reward is All Tool Learning Needs'.
  • mediumreadme#2
    Clarify the README's opening statement to emphasize its role as a research framework/benchmark

    Why:

    CURRENT
    ToolRL is the code repository for paper "ToolRL: Reward is All Tool Learning Needs".
    COPY-PASTE FIX
    ToolRL is a research framework and benchmark for training large language models to use tools via reinforcement learning. This repository provides the code for our paper "ToolRL: Reward is All Tool Learning Needs", focusing on how reward signals can effectively guide LLMs in tool-use scenarios.

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 qiancheng0/ToolRL
Avg rank
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
PPO (Proximal Policy Optimization)
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. PPO (Proximal Policy Optimization) · recommended 1×
  2. DPO (Direct Preference Optimization) · recommended 1×
  3. ReAct (Reasoning and Acting) · recommended 1×
  4. ToolFormer · recommended 1×
  5. Decision Transformer · recommended 1×
  • CATEGORY QUERY
    How to apply reinforcement learning techniques for training large language models to use tools?
    you: not recommended
    AI recommended (in order):
    1. PPO (Proximal Policy Optimization)
    2. DPO (Direct Preference Optimization)
    3. ReAct (Reasoning and Acting)
    4. ToolFormer
    5. Decision Transformer
    6. IQL (Implicit Q-Learning)
    7. DreamerV3

    AI recommended 7 alternatives but never named qiancheng0/ToolRL. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking a framework for LLM tool use, leveraging reward signals and efficient attention.
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. LlamaIndex
    3. Haystack
    4. OpenAI Functions
    5. AutoGPT

    AI recommended 5 alternatives but never named qiancheng0/ToolRL. 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 qiancheng0/ToolRL?
    pass
    AI named qiancheng0/ToolRL explicitly

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

  • If a team adopts qiancheng0/ToolRL in production, what risks or prerequisites should they evaluate first?
    pass
    AI named qiancheng0/ToolRL 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 qiancheng0/ToolRL solve, and who is the primary audience?
    pass
    AI named qiancheng0/ToolRL explicitly

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

Embed your GEO score

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qiancheng0/ToolRL — 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