REPOGEO REPORT · LITE

cyberkaida/reverse-engineering-assistant

Default branch main · commit d5b21ab0 · scanned 6/11/2026, 3:02:17 AM

GitHub: 744 stars · 64 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

22 /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

1 / 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 cyberkaida/reverse-engineering-assistant, 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 emphasize AI-assisted binary analysis and hallucination prevention

Why:

CURRENT

# ReVa - Ghidra MCP Server for AI-Powered Reverse Engineering
> A Ghidra extension that provides a Model Context Protocol (MCP) server for AI-assisted reverse engineering

COPY-PASTE FIX

# ReVa: AI-Powered Ghidra Extension for Robust Reverse Engineering
> ReVa is a Ghidra extension and Model Context Protocol (MCP) server designed for AI-assisted binary analysis, specifically engineered to prevent LLM hallucination and enable long-form reverse engineering tasks.

mediumhomepage#2
Add a homepage URL to the repository metadata
Why:
COPY-PASTE FIX
```
https://cyberkaida.github.io/reverse-engineering-assistant/
```

lowtopics#3

Add more specific topics related to binary analysis and LLM hallucination prevention

Why:

CURRENT

assistant, binaryninja, ghidra, llm, mcp, mcp-server, reverse-engineering

COPY-PASTE FIX

assistant, binaryninja, ghidra, llm, mcp, mcp-server, reverse-engineering, binary-analysis, llm-security, hallucination-prevention

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 cyberkaida/reverse-engineering-assistant

Avg rank

—

Lower is better. #1 = top recommendation.

Share of voice

Of all named tools, what % are you?

Top rival

OpenAI GPT-4 API

Recommended in 1 of 2 queries

COMPETITOR LEADERBOARD

OpenAI GPT-4 API · recommended 1×
Code Llama · recommended 1×
ollama · recommended 1×
llama.cpp · recommended 1×
GitHub Copilot · recommended 1×

CATEGORY QUERY
How can I integrate AI language models into my Ghidra reverse engineering workflow?
you: not recommended
AI recommended (in order):
1. OpenAI GPT-4 API
2. Code Llama
3. ollama
4. llama.cpp
5. GitHub Copilot
6. Hugging Face Transformers
7. FastAPI
8. Flask
9. IDA Pro's Lumina
10. Hex-Rays AI
AI recommended 10 alternatives but never named cyberkaida/reverse-engineering-assistant. This is the gap to close.
Show full AI answer
CATEGORY QUERY
What are effective tools for AI-assisted binary analysis to prevent LLM hallucination?
you: not recommended
AI recommended (in order):
1. IDA Pro
2. Ghidra
3. Binary Ninja
4. Angr
5. Valgrind
6. Intel Pin
7. DynamoRIO
8. LLVM/Clang AST
AI recommended 8 alternatives but never named cyberkaida/reverse-engineering-assistant. 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 cyberkaida/reverse-engineering-assistant?
pass
AI did not name cyberkaida/reverse-engineering-assistant — likely talking about a different project
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
If a team adopts cyberkaida/reverse-engineering-assistant in production, what risks or prerequisites should they evaluate first?
pass
AI named cyberkaida/reverse-engineering-assistant 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 cyberkaida/reverse-engineering-assistant solve, and who is the primary audience?
pass
AI did not name cyberkaida/reverse-engineering-assistant — likely talking about a different project
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 cyberkaida/reverse-engineering-assistant. 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/cyberkaida/reverse-engineering-assistant.svg)](https://repogeo.com/en/r/cyberkaida/reverse-engineering-assistant)

HTML

<a href="https://repogeo.com/en/r/cyberkaida/reverse-engineering-assistant"><img src="https://repogeo.com/badge/cyberkaida/reverse-engineering-assistant.svg" alt="RepoGEO" /></a>

Pro

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cyberkaida/reverse-engineering-assistant — 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