REPOGEO REPORT · LITE

rnchg/APT

Default branch master · commit 027e3d28 · scanned 6/30/2026, 9:46:49 PM

GitHub: 774 stars · 84 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

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 rnchg/APT, 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 H1 and opening paragraph to clarify 'APT'

Why:

CURRENT

# AI Productivity Tools

Free and open source, improve user productivity, protect privacy and data security. Provide efficient and convenient AI solutions, including but not limited to: built-in local exclusive ChatGPT, DeepSeek, Phi, Qwen and other models, one-click batch intelligent processing of pictures, videos, audio, etc.

COPY-PASTE FIX

# AI Productivity Tools (APT)

This project, 'APT,' is a free and open-source desktop application for AI productivity, not a package manager or system utility. It improves user productivity and protects privacy and data security by providing efficient and convenient AI solutions, including but not limited to: built-in local exclusive ChatGPT, DeepSeek, Phi, Qwen and other models, and one-click batch intelligent processing of pictures, videos, audio, etc.

mediumreadme#2

Add a dedicated section highlighting APT's combined value proposition

Why:

COPY-PASTE FIX

Add a new section, perhaps titled 'Why APT?', that explicitly states its unique combination of local LLM chat and batch media processing (images, video, audio) in a single, easy-to-use, offline desktop application, differentiating it from single-purpose tools like Ollama or FFmpeg.

lowhomepage#3
Add a homepage URL to the repository metadata
Why:
COPY-PASTE FIX
```
https://github.com/rnchg/APT (or a dedicated project website if one exists)
```

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 rnchg/APT

Avg rank

—

Lower is better. #1 = top recommendation.

Share of voice

Of all named tools, what % are you?

Top rival

Ollama

Recommended in 1 of 2 queries

COMPETITOR LEADERBOARD

Ollama · recommended 1×
LM Studio · recommended 1×
GPT4All · recommended 1×
Jan · recommended 1×
KoboldCpp · recommended 1×

CATEGORY QUERY
What tools enable running large language models locally for private, offline conversations?
you: not recommended
AI recommended (in order):
1. Ollama
2. LM Studio
3. GPT4All
4. Jan
5. KoboldCpp
6. text-generation-webui (oobabooga/text-generation-webui)
7. llama.cpp
AI recommended 7 alternatives but never named rnchg/APT. This is the gap to close.
Show full AI answer
CATEGORY QUERY
Seeking an open-source solution for intelligent batch processing of images, videos, and audio.
you: not recommended
AI recommended (in order):
1. FFmpeg (FFmpeg/FFmpeg)
2. ImageMagick (ImageMagick/ImageMagick)
3. GraphicsMagick (GraphicsMagick/GraphicsMagick)
4. OpenCV (opencv/opencv)
5. Celery (celery/celery)
6. RabbitMQ (rabbitmq/rabbitmq)
7. Redis (redis/redis)
8. TensorFlow (tensorflow/tensorflow)
9. PyTorch (pytorch/pytorch)
10. Audacity (audacity/audacity)
AI recommended 10 alternatives but never named rnchg/APT. 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 rnchg/APT?
pass
AI named rnchg/APT explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
If a team adopts rnchg/APT in production, what risks or prerequisites should they evaluate first?
pass
AI named rnchg/APT 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 rnchg/APT solve, and who is the primary audience?
pass
AI named rnchg/APT 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 rnchg/APT. 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)

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

HTML

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

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rnchg/APT — 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