RRepoGEO

REPOGEO REPORT · LITE

dnhkng/GLaDOS

Default branch main · commit 878b1443 · scanned 5/14/2026, 4:13:06 PM

GitHub: 5,545 stars · 431 forks

AI VISIBILITY SCORE
35 /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
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 dnhkng/GLaDOS, 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
  • highreadme#1
    Reposition README intro to clarify project category

    Why:

    COPY-PASTE FIX
    This project is a framework for building a real-life, personality-driven AI assistant inspired by GLaDOS from Valve's Portal series, leveraging modular cognitive agents for vision, memory, and tool use. It is not a general-purpose web framework.
  • mediumreadme#2
    Highlight recent development activity in the README

    Why:

    COPY-PASTE FIX
    Actively developed since 2022, this project has undergone multiple refactors since 2023 to integrate the latest LLM advancements, now featuring vision, memory, and tool use.

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 dnhkng/GLaDOS
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. OpenAI GPT-4 · recommended 1×
  3. GPT-3.5 Turbo · recommended 1×
  4. Hugging Face Transformers · recommended 1×
  5. Pinecone · recommended 1×
  • CATEGORY QUERY
    How to build an AI assistant with a unique, sarcastic personality?
    you: not recommended
    AI recommended (in order):
    1. OpenAI GPT-4
    2. GPT-3.5 Turbo
    3. LangChain
    4. Hugging Face Transformers
    5. Pinecone
    6. ChromaDB
    7. FastAPI
    8. Flask
    9. Docker

    AI recommended 9 alternatives but never named dnhkng/GLaDOS. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking libraries for building modular AI systems with specialized cognitive agents.
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. LlamaIndex
    3. Haystack
    4. AutoGen
    5. CrewAI
    6. OpenAI Assistants API

    AI recommended 6 alternatives but never named dnhkng/GLaDOS. 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 dnhkng/GLaDOS?
    pass
    AI named dnhkng/GLaDOS explicitly

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

  • If a team adopts dnhkng/GLaDOS in production, what risks or prerequisites should they evaluate first?
    pass
    AI named dnhkng/GLaDOS 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 dnhkng/GLaDOS solve, and who is the primary audience?
    pass
    AI named dnhkng/GLaDOS 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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MARKDOWN (README)
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dnhkng/GLaDOS — 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