REPOGEO REPORT · LITE

ydyjya/Awesome-LLM-Safety

Default branch main · commit 70571a03 · scanned 5/20/2026, 10:52:50 PM

GitHub: 1,848 stars · 104 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

17 /100

Critical

Category recall

0 / 2

Not recommended in any query

Rule findings

1 pass · 0 warn · 1 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 ydyjya/Awesome-LLM-Safety, 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 the README introduction to emphasize "awesome list"

Why:

CURRENT

Welcome to our Awesome-llm-safety repository! 🥰🥰🥰 We've curated a collection of the latest 😋, most comprehensive 😎, and most valuable 🤩 resources on large language model safety (llm-safety).

COPY-PASTE FIX

Welcome to **Awesome LLM-Safety**, the definitive curated list of papers, articles, datasets, and tools focused on Large Language Model (LLM) safety. We've gathered the latest, most comprehensive, and most valuable resources to serve as your central hub for LLM safety research and practice.

hightopics#2

Add relevant topics to the repository

Why:

COPY-PASTE FIX

llm-safety, large-language-models, llm, safety, ai-safety, machine-learning, awesome-list, research-papers, resources, curated-list, red-teaming, jailbreak, alignment, privacy, fairness

mediumlicense#3
Add a LICENSE file to the repository
Why:
COPY-PASTE FIX
```
Create a `LICENSE` file in the repository root containing the text of the MIT License.
```

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 ydyjya/Awesome-LLM-Safety

Avg rank

—

Lower is better. #1 = top recommendation.

Share of voice

Of all named tools, what % are you?

Top rival

AI Impacts

Recommended in 1 of 2 queries

COMPETITOR LEADERBOARD

AI Impacts · recommended 1×
80,000 Hours · recommended 1×
MIRI · recommended 1×
OpenAI · recommended 1×
Anthropic · recommended 1×

CATEGORY QUERY
Where can I find comprehensive resources and papers on large language model safety?
you: not recommended
AI recommended (in order):
1. AI Impacts
2. 80,000 Hours
3. MIRI
4. OpenAI
5. Anthropic
6. DeepMind
7. arXiv.org
8. Stanford HAI
9. AI Index Report
10. Center for AI Safety
AI recommended 10 alternatives but never named ydyjya/Awesome-LLM-Safety. This is the gap to close.
Show full AI answer
CATEGORY QUERY
What are the best practices and challenges for ensuring safety in LLM development?
you: not recommended
AI recommended (in order):
1. OpenAI's Content Moderation API
2. Hugging Face Datasets library
3. Snorkel
4. Garak
5. Anthropic's Constitutional AI principles
6. NeMo Guardrails (NVIDIA)
7. Microsoft Azure AI Content Safety
8. LangChain
9. LIME (Local Interpretable Model-agnostic Explanations)
10. SHAP (SHapley Additive exPlanations)
11. InterpretML (Microsoft)
12. Argilla
13. Weights & Biases
14. Datadog
15. Splunk
16. Google's AI Principles
17. NIST AI Risk Management Framework
AI recommended 17 alternatives but never named ydyjya/Awesome-LLM-Safety. This is the gap to close.
Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

Metadata completeness
fail
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 ydyjya/Awesome-LLM-Safety?
pass
AI did not name ydyjya/Awesome-LLM-Safety — 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 ydyjya/Awesome-LLM-Safety in production, what risks or prerequisites should they evaluate first?
pass
AI named ydyjya/Awesome-LLM-Safety 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 ydyjya/Awesome-LLM-Safety solve, and who is the primary audience?
pass
AI did not name ydyjya/Awesome-LLM-Safety — 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

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MARKDOWN (README)

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HTML

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ydyjya/Awesome-LLM-Safety — 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