RRepoGEO

REPOGEO REPORT · LITE

NVIDIA-NeMo/Guardrails

Default branch develop · commit 60ea7069 · scanned 5/17/2026, 10:46:03 PM

GitHub: 6,138 stars · 679 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
40 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
2 pass · 0 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 NVIDIA-NeMo/Guardrails, 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 opening to clarify 'toolkit' and 'programmable' nature

    Why:

    CURRENT
    NVIDIA NeMo Guardrails library is an open-source toolkit for easily adding *programmable guardrails* to LLM-based conversational applications.
    COPY-PASTE FIX
    NVIDIA NeMo Guardrails is an open-source **toolkit** for building **programmable guardrails** directly into LLM-based conversational systems and AI agents. Unlike simple content moderation APIs, NeMo Guardrails provides a comprehensive framework to define and enforce complex, multi-turn dialog flows, safety policies, and custom behaviors.
  • mediumtopics#2
    Add more specific topics for programmable AI agent guardrails

    Why:

    CURRENT
    agents, generative-ai, guardrails, llm-safety, llm-security, llms, nvidia, python, safety
    COPY-PASTE FIX
    agents, generative-ai, guardrails, llm-safety, llm-security, llms, nvidia, python, safety, ai-guardrails, programmable-guardrails, llm-toolkit, ai-agent-safety
  • lowlicense#3
    Clarify the project's license in the README

    Why:

    COPY-PASTE FIX
    NVIDIA NeMo Guardrails is licensed under the Apache 2.0 License. See the [LICENSE](LICENSE) file for details.

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 NVIDIA-NeMo/Guardrails
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
OpenAI Moderation API
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. OpenAI Moderation API · recommended 1×
  2. Azure AI Content Safety · recommended 1×
  3. Google Cloud's Perspective API · recommended 1×
  4. Amazon Rekognition · recommended 1×
  5. Amazon Comprehend · recommended 1×
  • CATEGORY QUERY
    How can I add programmable safety and content moderation to my LLM applications?
    you: not recommended
    AI recommended (in order):
    1. OpenAI Moderation API
    2. Azure AI Content Safety
    3. Google Cloud's Perspective API
    4. Amazon Rekognition
    5. Amazon Comprehend
    6. Cohere's Moderate API
    7. Hive Moderation API
    8. Bodyguard.ai

    AI recommended 8 alternatives but never named NVIDIA-NeMo/Guardrails. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking a Python toolkit to implement robust guardrails for AI agent safety and security.
    you: not recommended
    AI recommended (in order):
    1. Guardrails AI (guardrails-ai/guardrails)
    2. LangChain (langchain-ai/langchain)
    3. LlamaIndex (run-llama/llama_index)
    4. OpenAI Evals (openai/evals)
    5. Pydantic (pydantic/pydantic)
    6. NLTK (nltk/nltk)
    7. spaCy (explosion/spaCy)
    8. Hugging Face Transformers (huggingface/transformers)

    AI recommended 8 alternatives but never named NVIDIA-NeMo/Guardrails. This is the gap to close.

    Show full AI answer

Objective checks

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

  • Metadata completeness
    pass

  • 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 NVIDIA-NeMo/Guardrails?
    pass
    AI named NVIDIA-NeMo/Guardrails explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • If a team adopts NVIDIA-NeMo/Guardrails in production, what risks or prerequisites should they evaluate first?
    pass
    AI named NVIDIA-NeMo/Guardrails 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 NVIDIA-NeMo/Guardrails solve, and who is the primary audience?
    pass
    AI named NVIDIA-NeMo/Guardrails explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

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NVIDIA-NeMo/Guardrails — 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