RRepoGEO

REPOGEO REPORT · LITE

meta-llama/prompt-ops

Default branch main · commit f6ce9977 · scanned 6/11/2026, 6:42:54 PM

GitHub: 820 stars · 127 forks

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/prompt-ops, 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 improve categorization

    Why:

    CURRENT
    (none)
    COPY-PASTE FIX
    llm, prompt-engineering, prompt-optimization, machine-learning, artificial-intelligence, meta-ai, python
  • highreadme#2
    Clarify the repository's core purpose in the README's opening

    Why:

    CURRENT
    <h1 align="center"> Prompt Ops </h1>

### 🎉 New: Prompt Duel Optimizer (PDO) Published!
    COPY-PASTE FIX
    <h1 align="center"> Prompt Ops: An Open-Source Tool for LLM Prompt Optimization </h1>

This repository provides tools and methods for efficiently building, testing, and deploying optimized prompts for Large Language Models. It includes state-of-the-art techniques like the Prompt Duel Optimizer (PDO) for label-free prompt optimization.

### 🎉 New: Prompt Duel Optimizer (PDO) Published!
  • mediumhomepage#3
    Add a homepage URL to the repository's About section

    Why:

    CURRENT
    (none)
    COPY-PASTE FIX
    https://llama.developer.meta.com/

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/prompt-ops
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
LangChain
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. LangChain · recommended 2×
  2. LlamaIndex · recommended 2×
  3. OpenAI's GPT-4 · recommended 1×
  4. Anthropic's Claude · recommended 1×
  5. ROUGE · recommended 1×
  • CATEGORY QUERY
    How can I efficiently improve my LLM prompt performance without extensive manual labeling?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. LlamaIndex
    3. OpenAI's GPT-4
    4. Anthropic's Claude
    5. ROUGE
    6. BLEU
    7. BERTScore
    8. LLM-as-a-Judge
    9. LMQL
    10. Instructor

    AI recommended 10 alternatives but never named meta-llama/prompt-ops. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are effective techniques for automatically optimizing large language model prompts?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. LlamaIndex
    3. OpenAI API
    4. Humanloop
    5. W&B Prompts
    6. PromptPerfect
    7. Auto-GPT
    8. BabyAGI
    9. MLflow
    10. DeepEval

    AI recommended 10 alternatives but never named meta-llama/prompt-ops. 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/prompt-ops?
    pass
    AI named meta-llama/prompt-ops 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/prompt-ops in production, what risks or prerequisites should they evaluate first?
    pass
    AI named meta-llama/prompt-ops 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/prompt-ops solve, and who is the primary audience?
    pass
    AI named meta-llama/prompt-ops explicitly

    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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meta-llama/prompt-ops — 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