RRepoGEO

REPOGEO REPORT · LITE

asinghcsu/AgenticRAG-Survey

Default branch main · commit 1d91e657 · scanned 5/11/2026, 7:37:41 AM

GitHub: 1,601 stars · 178 forks

AI VISIBILITY SCORE
22 /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
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 asinghcsu/AgenticRAG-Survey, 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 that the repo is a survey, not a framework, in the README's opening

    Why:

    COPY-PASTE FIX
    This repository is the official companion to our comprehensive survey paper, 'Agentic Retrieval-Augmented Generation (Agentic RAG),' providing an academic overview and taxonomy of the field, not a production-ready library or framework.
  • highlicense#2
    Add a LICENSE file to the repository

    Why:

    COPY-PASTE FIX
    Create a `LICENSE` file in the repository root with the chosen open-source license (e.g., MIT, Apache-2.0, or CC-BY-4.0 for content).
  • mediumtopics#3
    Add topics that clarify the repository's format as a survey or research paper

    Why:

    CURRENT
    agentic, agentic-ai, agentic-framework, agentic-pattern, agentic-rag, agentic-workflow, llm-agent, multi-agent-systems, multiagent, rag, reflection, tools
    COPY-PASTE FIX
    agentic, agentic-ai, agentic-framework, agentic-pattern, agentic-rag, agentic-workflow, llm-agent, multi-agent-systems, multiagent, rag, reflection, tools, survey, research, academic-paper, literature-review

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 asinghcsu/AgenticRAG-Survey
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
LangChain
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. LangChain · recommended 1×
  2. LlamaIndex · recommended 1×
  3. AutoGPT · recommended 1×
  4. BabyAGI · recommended 1×
  5. Haystack · recommended 1×
  • CATEGORY QUERY
    How can I enhance my RAG pipeline with autonomous AI agents for better performance?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. LlamaIndex
    3. AutoGPT
    4. BabyAGI
    5. Haystack
    6. CrewAI
    7. Microsoft AutoGen

    AI recommended 7 alternatives but never named asinghcsu/AgenticRAG-Survey. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are the different agentic patterns and multi-agent system architectures for advanced RAG?
    you: not recommended
    AI recommended (in order):
    1. LangChain (langchain-ai/langchain)
    2. LlamaIndex (run-llama/llama_index)
    3. OpenAI
    4. DSPy (stanfordnlp/dspy)
    5. LangGraph (langchain-ai/langgraph)
    6. AutoGen (microsoft/autogen)
    7. CrewAI (joaomdmoura/crewai)

    AI recommended 7 alternatives but never named asinghcsu/AgenticRAG-Survey. 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 asinghcsu/AgenticRAG-Survey?
    pass
    AI did not name asinghcsu/AgenticRAG-Survey — 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 asinghcsu/AgenticRAG-Survey in production, what risks or prerequisites should they evaluate first?
    pass
    AI named asinghcsu/AgenticRAG-Survey 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 asinghcsu/AgenticRAG-Survey solve, and who is the primary audience?
    pass
    AI did not name asinghcsu/AgenticRAG-Survey — 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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asinghcsu/AgenticRAG-Survey — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

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  • Brand-free category queries5 vs 2 in Lite
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