RRepoGEO

REPOGEO REPORT · LITE

InternScience/InternAgent

Default branch main · commit e341f8f1 · scanned 5/23/2026, 6:42:52 AM

GitHub: 1,308 stars · 116 forks

Scan history for this repo

Score trend below includes all ready runs (older left, newer right; scroll horizontally if needed). The table is collapsed by default—expand for newest-first rows, 10 per page.

Score trend (left → right: older → newer)

2 ready scans. Expand the table below for newest-first rows (10 per page, paginated).

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 InternScience/InternAgent, 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
    Add a disambiguation sentence in the README's opening to clarify 'InternAgent' is not about internships.

    Why:

    CURRENT
    # InternAgent-1.5: A Unified Agentic Framework for Long-Horizon Autonomous Scientific Discovery
    COPY-PASTE FIX
    # InternAgent-1.5: A Unified Agentic Framework for Long-Horizon Autonomous Scientific Discovery

> Note: InternAgent refers to an 'internal agent' for scientific research, not an internship platform.
  • mediumcomparison#2
    Add a comparison section to differentiate from generic agent frameworks.

    Why:

    COPY-PASTE FIX
    Add a new section, e.g., '## Why InternAgent? (vs. Generic Agent Frameworks)', that highlights its unique focus on scientific discovery, specific benchmarks (GAIA, HLE, GPQA, FrontierScience), and support for physical/wet-lab experiments, differentiating it from general-purpose agent frameworks.
  • lowlicense#3
    Clarify the existing license(s) in the README.

    Why:

    COPY-PASTE FIX
    Add a section to the README, e.g., '## License\nThis project is licensed under [describe the license(s) present in the LICENSE file, e.g., 'a custom license combining elements of X and Y']. Please refer to the [LICENSE](LICENSE) file for full details.'

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 InternScience/InternAgent
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Significant-Gravitas/AutoGPT
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Significant-Gravitas/AutoGPT · recommended 1×
  2. yoheinakajima/babyagi · recommended 1×
  3. geekan/MetaGPT · recommended 1×
  4. langchain-ai/langchain · recommended 1×
  5. joaomdmoura/crewai · recommended 1×
  • CATEGORY QUERY
    What agentic framework can automate long-horizon scientific discovery and hypothesis generation?
    you: not recommended
    AI recommended (in order):
    1. AutoGPT (Significant-Gravitas/AutoGPT)
    2. BabyAGI (yoheinakajima/babyagi)
    3. MetaGPT (geekan/MetaGPT)
    4. LangChain Agents (langchain-ai/langchain)
    5. CrewAI (joaomdmoura/crewai)
    6. Open Interpreter (KillianLucas/open-interpreter)

    AI recommended 6 alternatives but never named InternScience/InternAgent. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking a multi-agent system for autonomous scientific paper reproduction and algorithm design tasks.
    you: not recommended
    AI recommended (in order):
    1. AutoGPT
    2. LangChain
    3. CrewAI
    4. OpenAI Assistants API
    5. MAD Framework
    6. SPADE

    AI recommended 6 alternatives but never named InternScience/InternAgent. 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 InternScience/InternAgent?
    pass
    AI named InternScience/InternAgent explicitly

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

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

    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 InternScience/InternAgent. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

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MARKDOWN (README)
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HTML
<a href="https://repogeo.com/en/r/InternScience/InternAgent"><img src="https://repogeo.com/badge/InternScience/InternAgent.svg" alt="RepoGEO" /></a>
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InternScience/InternAgent — 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