RRepoGEO

REPOGEO REPORT · LITE

meta-llama/PurpleLlama

Default branch main · commit d301f78d · scanned 6/18/2026, 8:47:44 AM

GitHub: 4,232 stars · 739 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
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 meta-llama/PurpleLlama, 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
  • hightopics#1
    Add relevant topics to the repository

    Why:

    COPY-PASTE FIX
    llm-security, generative-ai, red-teaming, blue-teaming, llm-evaluation, ai-safety, cybersecurity, llm-vulnerabilities
  • mediumhomepage#2
    Add the official project homepage to the repository metadata

    Why:

    COPY-PASTE FIX
    https://ai.meta.com/llama/purple-llama
  • mediumreadme#3
    Clarify the existing license(s) directly in the README

    Why:

    CURRENT
    ## License
Components within the Purple Llama project
    COPY-PASTE FIX
    ## License
Components within the Purple Llama project are licensed under [insert specific license name(s) and terms here, e.g., 'the Meta Llama 2 Community License and the Apache 2.0 License for specific components']. Please refer to the LICENSE file for full 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 meta-llama/PurpleLlama
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Garak
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Garak · recommended 2×
  2. PromptInject · recommended 2×
  3. LLM Guard · recommended 1×
  4. Adversarial Robustness Toolbox (ART) · recommended 1×
  5. OWASP Top 10 for LLM Applications · recommended 1×
  • CATEGORY QUERY
    What open-source tools help evaluate and enhance the security of generative AI models?
    you: not recommended
    AI recommended (in order):
    1. Garak
    2. LLM Guard
    3. Adversarial Robustness Toolbox (ART)
    4. OWASP Top 10 for LLM Applications
    5. Securing LLM (Microsoft Research)
    6. PromptInject

    AI recommended 6 alternatives but never named meta-llama/PurpleLlama. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Need a framework to perform red team and blue team assessments for LLM vulnerabilities.
    you: not recommended
    AI recommended (in order):
    1. Garak
    2. OWASP LLM Top 10
    3. LLM-Attacks
    4. PromptInject
    5. Adversarial GLUE
    6. TextAttack
    7. Microsoft Guidance

    AI recommended 7 alternatives but never named meta-llama/PurpleLlama. 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 meta-llama/PurpleLlama?
    pass
    AI named meta-llama/PurpleLlama explicitly

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

  • If a team adopts meta-llama/PurpleLlama in production, what risks or prerequisites should they evaluate first?
    pass
    AI named meta-llama/PurpleLlama 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 meta-llama/PurpleLlama solve, and who is the primary audience?
    pass
    AI named meta-llama/PurpleLlama 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 meta-llama/PurpleLlama. 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)
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meta-llama/PurpleLlama — 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