REPOGEO REPORT · LITE

dnhkng/GLaDOS

Default branch main · commit c0648ca9 · scanned 6/25/2026, 5:43:28 AM

GitHub: 5,602 stars · 440 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)

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

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

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 the repository

Why:

COPY-PASTE FIX

ai, multi-agent, conversational-ai, llm, personality-core, glados, portal, valve, python, voice-synthesis, tool-use, vision

highreadme#2

Reposition the README's opening to explicitly state the project's core purpose

Why:

CURRENT

# GLaDOS Personality Core

## Prologue

> *"Science isn't about asking why. It's about asking, 'Why not?'"  -  Cave Johnson*

GLaDOS is the AI antagonist from Valve's Portal series—a sardonic, passive-aggressive superintelligence who views humans as test subjects worthy of both study and mockery.

COPY-PASTE FIX

# GLaDOS Personality Core

This repository implements a multi-agent AI system designed to emulate the GLaDOS personality core, focusing on low-latency conversational responses, vision, memory, and tool use.

## Prologue

> *"Science isn't about asking why. It's about asking, 'Why not?'"  -  Cave Johnson*

GLaDOS is the AI antagonist from Valve's Portal series—a sardonic, passive-aggressive superintelligence who views humans as test subjects worthy of both study and mockery.

mediumhomepage#3
Add a homepage URL to the repository metadata
Why:
COPY-PASTE FIX
```
https://github.com/dnhkng/GLaDOS
```

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

Of all named tools, what % are you?

Top rival

langchain-ai/langchain

Recommended in 2 of 2 queries

COMPETITOR LEADERBOARD

langchain-ai/langchain · recommended 2×
OpenAI GPT-4 / GPT-3.5 Turbo · recommended 1×
huggingface/transformers · recommended 1×
deepmipt/DeepPavlov · recommended 1×
RasaHQ/rasa · recommended 1×

CATEGORY QUERY
How to build a custom AI assistant with a distinct, sarcastic personality?
you: not recommended
AI recommended (in order):
1. OpenAI GPT-4 / GPT-3.5 Turbo
2. Hugging Face Transformers (huggingface/transformers)
3. LangChain (langchain-ai/langchain)
4. DeepPavlov (deepmipt/DeepPavlov)
5. Rasa (RasaHQ/rasa)
6. Google Cloud's Vertex AI
7. ElevenLabs
AI recommended 7 alternatives but never named dnhkng/GLaDOS. This is the gap to close.
Show full AI answer
CATEGORY QUERY
What frameworks enable multi-agent AI systems for low-latency conversational responses?
you: not recommended
AI recommended (in order):
1. LangChain (langchain-ai/langchain)
2. LlamaIndex (run-llama/llama_index)
3. Haystack (deepset-ai/haystack)
4. AutoGen (microsoft/autogen)
5. CrewAI (joaomdmoura/crewai)
6. SPADE (javipalanca/spade)
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)

[![RepoGEO](https://repogeo.com/badge/dnhkng/GLaDOS.svg)](https://repogeo.com/en/r/dnhkng/GLaDOS)

HTML

<a href="https://repogeo.com/en/r/dnhkng/GLaDOS"><img src="https://repogeo.com/badge/dnhkng/GLaDOS.svg" alt="RepoGEO" /></a>

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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