RRepoGEO

REPOGEO REPORT · LITE

Human-Agent-Society/CORAL

Default branch main · commit 4a302485 · scanned 6/13/2026, 6:16:58 PM

GitHub: 722 stars · 94 forks

AI VISIBILITY SCORE
40 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
2 pass · 0 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 Human-Agent-Society/CORAL, 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
    Reposition README's first sentence to emphasize code evolution

    Why:

    CURRENT
    CORAL is infrastructure for **autonomous AI agent organizations** that run experiments, share knowledge, and continuously improve solutions.
    COPY-PASTE FIX
    CORAL is infrastructure for **autonomous AI agent organizations** that collaboratively **evolve and improve code solutions**, run experiments, share knowledge, and continuously improve software.
  • mediumcomparison#2
    Add a 'Comparison to Alternatives' section in the README

    Why:

    COPY-PASTE FIX
    Add a new section, e.g., `## Comparison to Alternatives`, explaining how CORAL differs from broader agent frameworks like AutoGPT, LangChain, and LlamaIndex by focusing on autonomous self-evolution for code, autoresearch, and robust evaluation of software solutions. Leverage the AI's own differentiation: 'CORAL's core differentiator is its explicit design as a platform for orchestrating multiple LLM-powered agents under human guidance to collaboratively solve complex, open-ended problems.'
  • lowexamples#3
    Expand and highlight practical examples in the README

    Why:

    COPY-PASTE FIX
    Ensure the `## Examples` section in the README includes at least 2-3 concrete, copy-pasteable examples demonstrating how CORAL is used for self-evolving code, autoresearch, or improving LLM coding agents, with clear steps and expected outcomes.

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 Human-Agent-Society/CORAL
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
AutoGPT
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. AutoGPT · recommended 2×
  2. LangChain · recommended 2×
  3. LlamaIndex · recommended 2×
  4. Docker · recommended 2×
  5. AgentGPT · recommended 1×
  • CATEGORY QUERY
    How can I set up an autonomous multi-agent system for self-evolving code solutions?
    you: not recommended
    AI recommended (in order):
    1. AutoGPT
    2. AgentGPT
    3. SuperAGI
    4. MetaGPT
    5. LangChain
    6. LlamaIndex
    7. OpenAI Assistants API
    8. Hugging Face Transformers Agents
    9. RLlib
    10. DeepMind's AlphaCode
    11. GPT-4
    12. Claude 3 Opus
    13. Google Gemini Advanced
    14. Docker
    15. Jupyter Notebooks
    16. Pytest
    17. JUnit
    18. Jest
    19. Git

    AI recommended 19 alternatives but never named Human-Agent-Society/CORAL. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What frameworks exist for building and evaluating self-improving LLM coding agents?
    you: not recommended
    AI recommended (in order):
    1. AutoGPT
    2. LangChain
    3. LlamaIndex
    4. OpenAI Evals
    5. Humanloop
    6. SWE-bench
    7. Docker

    AI recommended 7 alternatives but never named Human-Agent-Society/CORAL. This is the gap to close.

    Show full AI answer

Objective checks

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

  • Metadata completeness
    pass

  • 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 Human-Agent-Society/CORAL?
    pass
    AI named Human-Agent-Society/CORAL explicitly

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

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

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

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Human-Agent-Society/CORAL — 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