RRepoGEO

REPOGEO REPORT · LITE

sarthakrastogi/quality-prompts

Default branch main · commit bf851f56 · scanned 6/16/2026, 4:07:25 AM

GitHub: 730 stars · 46 forks

AI VISIBILITY SCORE
30 /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
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 sarthakrastogi/quality-prompts, 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.

OVERALL DIRECTION
  • highabout#1
    Add a concise repository description

    Why:

    COPY-PASTE FIX
    A Python library implementing 58 prompt engineering techniques for LLMs, enabling quick application and evaluation of advanced prompting strategies.
  • mediumreadme#2
    Clarify the library's scope and differentiate from frameworks in the README

    Why:

    CURRENT
    Quality Prompts implements 58 prompting techniques explained in this survey from the University of Maryland in collaboration with researchers from Learn Prompting, OpenAI, Microsoft, etc.
    COPY-PASTE FIX
    Quality Prompts is a Python library that implements 58 advanced prompting techniques, as explained in a comprehensive survey from the University of Maryland. Unlike full-stack frameworks, this library focuses specifically on providing ready-to-use, evaluable implementations of diverse prompting strategies to enhance your LLM interactions.

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 sarthakrastogi/quality-prompts
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
PromptLayer
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. PromptLayer · recommended 2×
  2. LangChain · recommended 1×
  3. LlamaIndex · recommended 1×
  4. Weights & Biases (W&B) Prompts · recommended 1×
  5. Humanloop · recommended 1×
  • CATEGORY QUERY
    What tools help apply and evaluate various prompt engineering techniques for large language models?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. LlamaIndex
    3. Weights & Biases (W&B) Prompts
    4. Humanloop
    5. OpenAI Playground / Azure OpenAI Studio
    6. Guardrails AI
    7. PromptLayer

    AI recommended 7 alternatives but never named sarthakrastogi/quality-prompts. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    How can I easily integrate and manage few-shot examples within my LLM prompt structures?
    you: not recommended
    AI recommended (in order):
    1. LangChain (langchain-ai/langchain)
    2. LlamaIndex (run-llama/llama_index)
    3. Haystack (deepset-ai/haystack)
    4. PromptLayer
    5. OpenAI API
    6. Weights & Biases Prompts (wandb/wandb)

    AI recommended 6 alternatives but never named sarthakrastogi/quality-prompts. 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 sarthakrastogi/quality-prompts?
    pass
    AI named sarthakrastogi/quality-prompts explicitly

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

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

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

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sarthakrastogi/quality-prompts — 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