RRepoGEO

REPOGEO REPORT · LITE

OPPO-PersonalAI/Agent_Foundation_Models

Default branch main · commit 9a6594d4 · scanned 6/11/2026, 6:32:41 AM

GitHub: 575 stars · 44 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 OPPO-PersonalAI/Agent_Foundation_Models, 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 improve categorization

    Why:

    COPY-PASTE FIX
    llm-agents, agent-foundation-models, multi-agent-systems, agentic-rl, llm-reasoning, end-to-end-ai, multi-agent-distillation
  • highreadme#2
    Clarify the unique value proposition in the README's opening paragraph

    Why:

    CURRENT
    This is the official repository for our paper "Chain-of-Agents: End-to-End Agent Foundation Models via Multi-Agent Distillation and Agentic RL". Our work introduces a novel paradigm for LLM reasoning that enables end-to-end complex problem-solving within a single model, simulating multi-agent collaboration through dynamic activation of tool agents and role-playing agents.
    COPY-PASTE FIX
    Chain-of-Agents introduces a novel paradigm for building **End-to-End Agent Foundation Models (AFM)**. Unlike traditional multi-agent systems that rely on complex frameworks, Chain-of-Agents enables a *single LLM* to solve complex problems by simulating multi-agent collaboration through dynamic activation of tool and role-playing agents, trained via multi-agent distillation and agentic reinforcement learning.
  • mediumhomepage#3
    Add the project homepage URL

    Why:

    COPY-PASTE FIX
    https://chain-of-agents-afm.github.io/

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 OPPO-PersonalAI/Agent_Foundation_Models
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. CrewAI · recommended 2×
  4. AutoGPT · recommended 1×
  5. BabyAGI · recommended 1×
  • CATEGORY QUERY
    How to achieve end-to-end complex problem-solving with a single LLM agent?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. LlamaIndex
    3. AutoGPT
    4. BabyAGI
    5. CrewAI
    6. Open Interpreter
    7. Microsoft's AutoGen

    AI recommended 7 alternatives but never named OPPO-PersonalAI/Agent_Foundation_Models. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are the best frameworks for simulating multi-agent LLM collaboration without complex prompt engineering?
    you: not recommended
    AI recommended (in order):
    1. AutoGen
    2. CrewAI
    3. LangChain
    4. LlamaIndex
    5. Haystack

    AI recommended 5 alternatives but never named OPPO-PersonalAI/Agent_Foundation_Models. 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 OPPO-PersonalAI/Agent_Foundation_Models?
    pass
    AI did not name OPPO-PersonalAI/Agent_Foundation_Models — 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 OPPO-PersonalAI/Agent_Foundation_Models in production, what risks or prerequisites should they evaluate first?
    pass
    AI named OPPO-PersonalAI/Agent_Foundation_Models 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 OPPO-PersonalAI/Agent_Foundation_Models solve, and who is the primary audience?
    pass
    AI did not name OPPO-PersonalAI/Agent_Foundation_Models — 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?

Embed your GEO score

Drop this badge into the README of OPPO-PersonalAI/Agent_Foundation_Models. 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/OPPO-PersonalAI/Agent_Foundation_Models.svg)](https://repogeo.com/en/r/OPPO-PersonalAI/Agent_Foundation_Models)
HTML
<a href="https://repogeo.com/en/r/OPPO-PersonalAI/Agent_Foundation_Models"><img src="https://repogeo.com/badge/OPPO-PersonalAI/Agent_Foundation_Models.svg" alt="RepoGEO" /></a>
Pro

Subscribe to Pro for deep diagnoses

OPPO-PersonalAI/Agent_Foundation_Models — 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