RRepoGEO

REPOGEO REPORT · LITE

openai/plugins-quickstart

Default branch main · commit 0763ac2b · scanned 6/20/2026, 10:17:41 PM

GitHub: 4,237 stars · 706 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 openai/plugins-quickstart, 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 the README's opening to clarify current relevance of plugins

    Why:

    CURRENT
    Get a TODO list ChatGPT plugin up and running in under 5 minutes using Python. This plugin is designed to work in conjunction with the ChatGPT plugins documentation. Plugins have been superseded by GPTs, learn more about creating a GPT with actions.
    COPY-PASTE FIX
    This quickstart helps you get a TODO list ChatGPT plugin up and running in under 5 minutes using Python. It's designed to work in conjunction with the ChatGPT plugins documentation, primarily for understanding existing plugin architectures or for specific use cases where plugins remain relevant. While plugins have been largely superseded by GPTs, this guide provides a foundational example.
  • mediumtopics#2
    Expand topics to include broader AI integration and quickstart terms

    Why:

    CURRENT
    chatgpt, chatgpt-plugins
    COPY-PASTE FIX
    chatgpt, chatgpt-plugins, ai-plugins, llm-plugins, chatbot-integration, quickstart, python-plugin
  • mediumreadme#3
    Add a 'Context and Alternatives' section to the README

    Why:

    COPY-PASTE FIX
    ## Context and Alternatives

This quickstart focuses specifically on building and deploying a basic ChatGPT plugin. While broader frameworks like LangChain or LlamaIndex offer extensive tools for LLM application development, this repository provides a direct, minimal example for the ChatGPT plugin architecture. For new projects, consider exploring GPTs with Actions, which have largely superseded plugins for extending ChatGPT's capabilities.

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 openai/plugins-quickstart
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
langchain-ai/langchain
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. langchain-ai/langchain · recommended 2×
  2. pallets/flask · recommended 2×
  3. OpenAI Plugins · recommended 1×
  4. run-llama/llama_index · recommended 1×
  5. microsoft/semantic-kernel · recommended 1×
  • CATEGORY QUERY
    How to quickly build a custom plugin for a large language model assistant?
    you: not recommended
    AI recommended (in order):
    1. OpenAI Plugins
    2. LangChain (langchain-ai/langchain)
    3. LlamaIndex (run-llama/llama_index)
    4. Semantic Kernel (microsoft/semantic-kernel)
    5. FastAPI (tiangolo/fastapi)
    6. Flask (pallets/flask)
    7. Node.js with Express.js (expressjs/express)

    AI recommended 7 alternatives but never named openai/plugins-quickstart. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are the best Python frameworks for integrating custom actions with AI chatbots?
    you: not recommended
    AI recommended (in order):
    1. Rasa Open Source (RasaHQ/rasa)
    2. LangChain (langchain-ai/langchain)
    3. Haystack (deepset-ai/haystack)
    4. OpenAI Assistants API (openai/openai-python)
    5. Flask (pallets/flask)
    6. Django (django/django)
    7. python-telegram-bot (python-telegram-bot/python-telegram-bot)
    8. discord.py (Rapptz/discord.py)
    9. slack_sdk (slackapi/python-slack-sdk)
    10. Botpress (botpress/botpress)

    AI recommended 10 alternatives but never named openai/plugins-quickstart. 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 openai/plugins-quickstart?
    pass
    AI named openai/plugins-quickstart explicitly

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

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

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

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  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite