REPOGEO REPORT · LITE
jplhughes/bon-jailbreaking
Default branch main · commit c1182103 · scanned 6/5/2026, 6:07:35 PM
GitHub: 567 stars · 96 forks
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 jplhughes/bon-jailbreaking, 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.
- hightopics#1Add specific topics for LLM red-teaming and jailbreaking
Why:
COPY-PASTE FIXllm, jailbreaking, red-teaming, adversarial-attacks, large-language-models, ai-safety, nlp, prompt-engineering
- mediumreadme#2Explicitly state the project's use case for red-teaming and LLM defense evaluation
Why:
COPY-PASTE FIXAdd a new section or integrate into the introduction: "**Use Cases:** This project is ideal for researchers and red-teamers focused on evaluating the robustness of LLM safety mechanisms, exploring adversarial attack techniques, and understanding the vulnerabilities of large language models. It implements the Best-of-N methodology described in our associated research paper."
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.
- Garak · recommended 1×
- AdvBench · recommended 1×
- OWASP LLM Top 10 · recommended 1×
- PromptInject · recommended 1×
- OpenAI API · recommended 1×
- CATEGORY QUERYWhat are effective techniques for bypassing safety guardrails in large language models?you: not recommended
Show full AI answer
- CATEGORY QUERYLooking for tools to red-team and evaluate the robustness of LLM defenses.you: not recommendedAI recommended (in order):
- Garak
- AdvBench
- OWASP LLM Top 10
- PromptInject
- OpenAI API
- Hugging Face Transformers
AI recommended 6 alternatives but never named jplhughes/bon-jailbreaking. This is the gap to close.
Show full AI answer
Objective checks
Rule-based audits of metadata signals AI engines weight most.
- Metadata completenesswarn
Suggestion:
- README presencepass
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 jplhughes/bon-jailbreaking?passAI named jplhughes/bon-jailbreaking explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
- If a team adopts jplhughes/bon-jailbreaking in production, what risks or prerequisites should they evaluate first?passAI named jplhughes/bon-jailbreaking 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 jplhughes/bon-jailbreaking solve, and who is the primary audience?passAI named jplhughes/bon-jailbreaking 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 jplhughes/bon-jailbreaking. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.
Live preview[](https://repogeo.com/en/r/jplhughes/bon-jailbreaking)<a href="https://repogeo.com/en/r/jplhughes/bon-jailbreaking"><img src="https://repogeo.com/badge/jplhughes/bon-jailbreaking.svg" alt="RepoGEO" /></a>Subscribe to Pro for deep diagnoses
jplhughes/bon-jailbreaking — 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