RRepoGEO

REPOGEO REPORT · LITE

microsoft/PromptWizard

Default branch main · commit a1d43f87 · scanned 6/30/2026, 6:21:43 AM

GitHub: 3,893 stars · 337 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
28 /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
2 / 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 microsoft/PromptWizard, 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
  • highreadme#1
    Reposition the README's opening to clearly state its purpose and category

    Why:

    CURRENT
    PromptWizard is a discrete prompt optimization framework that employs a self-evolving mechanism where the LLM generates, critiques, and refines its own prompts and examples, continuously improving through iterative feedback and synthesis. This self-adaptive approach ensures holistic optimization by evolving both the instructions and in-context learning examples for better task performance.
    COPY-PASTE FIX
    PromptWizard is a cutting-edge, task-aware prompt optimization framework designed for AI developers and prompt engineers. It uniquely employs a self-evolving mechanism where large language models (LLMs) generate, critique, and refine their own prompts and examples, continuously improving through iterative feedback and synthesis for superior task performance.
  • mediumhomepage#2
    Add the project website as the repository homepage

    Why:

    COPY-PASTE FIX
    https://microsoft.github.io/PromptWizard/

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 microsoft/PromptWizard
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Weights & Biases Prompts
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Weights & Biases Prompts · recommended 1×
  2. langchain-ai/langchain · recommended 1×
  3. openai/evals · recommended 1×
  4. PromptPerfect · recommended 1×
  5. Vellum · recommended 1×
  • CATEGORY QUERY
    How can I automatically refine and optimize my large language model prompts?
    you: not recommended
    AI recommended (in order):
    1. Weights & Biases Prompts
    2. LangChain (langchain-ai/langchain)
    3. OpenAI Evals (openai/evals)
    4. PromptPerfect
    5. Vellum
    6. MLflow (mlflow/mlflow)
    7. Comet ML

    AI recommended 7 alternatives but never named microsoft/PromptWizard. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What tools help LLMs self-critique and improve their own prompts and examples?
    you: not recommended
    AI recommended (in order):
    1. OpenAI Evals
    2. LangChain
    3. LlamaIndex
    4. Weights & Biases (W&B) Prompts
    5. Humanloop
    6. Guidance (Microsoft)

    AI recommended 6 alternatives but never named microsoft/PromptWizard. 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 microsoft/PromptWizard?
    pass
    AI did not name microsoft/PromptWizard — 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 microsoft/PromptWizard in production, what risks or prerequisites should they evaluate first?
    pass
    AI named microsoft/PromptWizard 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 microsoft/PromptWizard solve, and who is the primary audience?
    pass
    AI named microsoft/PromptWizard 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 microsoft/PromptWizard. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

RepoGEO badge previewLive preview
MARKDOWN (README)
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HTML
<a href="https://repogeo.com/en/r/microsoft/PromptWizard"><img src="https://repogeo.com/badge/microsoft/PromptWizard.svg" alt="RepoGEO" /></a>
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microsoft/PromptWizard — 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
microsoft/PromptWizard — RepoGEO report