REPOGEO REPORT · LITE

nicobailon/visual-explainer

Default branch main · commit 8f1d0e38 · scanned 5/28/2026, 5:41:47 AM

GitHub: 8,597 stars · 577 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 nicobailon/visual-explainer, 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 agent output scope

Why:

CURRENT

# visual-explainer

**An agent skill that turns complex terminal output into styled HTML pages you actually want to read.**

COPY-PASTE FIX

# visual-explainer: Rich HTML Explanations for AI Agent Output

**An agent skill that transforms raw terminal output from any AI agent into styled, interactive HTML pages or slide decks, making complex diagrams, diff reviews, plan audits, and data tables genuinely readable.**

hightopics#2

Add relevant topics for AI agent skills and output

Why:

CURRENT

(none)

COPY-PASTE FIX

ai-agent, agent-skill, generative-ai, html-reports, data-visualization, diagramming, code-review, terminal-output

mediumreadme#3

Add a 'Comparison to X' section in README

Why:

COPY-PASTE FIX

## Comparison to General Visualization Tools (Streamlit, Jupyter, Plotly Dash)

Unlike general-purpose data visualization libraries or notebook environments, visual-explainer is specifically designed as an **agent skill** to transform raw, unstructured terminal output into structured, styled HTML. It's not for building dashboards or interactive data apps from scratch, but rather for upgrading the readability and interactivity of explanations, diagrams, and data comparisons *generated by an AI agent*. Think of it as an intelligent rendering engine for your agent's insights, not a standalone development framework.

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 nicobailon/visual-explainer

Avg rank

—

Lower is better. #1 = top recommendation.

Share of voice

Of all named tools, what % are you?

Top rival

Streamlit

Recommended in 2 of 2 queries

COMPETITOR LEADERBOARD

Streamlit · recommended 2×
Plotly Dash · recommended 2×
Matplotlib · recommended 1×
Seaborn · recommended 1×
Jupyter Notebooks/Lab · recommended 1×

CATEGORY QUERY
How to visualize complex AI agent output beyond basic terminal text and ASCII diagrams?
you: not recommended
AI recommended (in order):
1. Streamlit
2. Plotly Dash
3. Matplotlib
4. Seaborn
5. Jupyter Notebooks/Lab
6. TensorBoard
7. Unity
8. Unreal Engine
9. ML-Agents
10. Pygame
11. Pyglet
12. D3.js
13. Flask
14. FastAPI
AI recommended 14 alternatives but never named nicobailon/visual-explainer. This is the gap to close.
Show full AI answer
CATEGORY QUERY
Tool to generate interactive HTML reports or slide decks from code analysis or data comparisons?
you: not recommended
AI recommended (in order):
1. Jupyter Notebook/JupyterLab
2. nbconvert
3. R Markdown
4. RStudio
5. flexdashboard
6. ioslides
7. Shiny
8. Plotly Dash
9. Streamlit
10. Quarto
11. Observable Notebooks
12. Power BI
13. Tableau
AI recommended 13 alternatives but never named nicobailon/visual-explainer. 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 nicobailon/visual-explainer?
pass
AI named nicobailon/visual-explainer explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
If a team adopts nicobailon/visual-explainer in production, what risks or prerequisites should they evaluate first?
pass
AI named nicobailon/visual-explainer 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 nicobailon/visual-explainer solve, and who is the primary audience?
pass
AI named nicobailon/visual-explainer 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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Live preview

MARKDOWN (README)

[![RepoGEO](https://repogeo.com/badge/nicobailon/visual-explainer.svg)](https://repogeo.com/en/r/nicobailon/visual-explainer)

HTML

<a href="https://repogeo.com/en/r/nicobailon/visual-explainer"><img src="https://repogeo.com/badge/nicobailon/visual-explainer.svg" alt="RepoGEO" /></a>

Pro

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nicobailon/visual-explainer — 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