RRepoGEO

REPOGEO REPORT · LITE

MIATECHPARTNERS/PromptChains

Default branch main · commit 22ac79a2 · scanned 5/20/2026, 9:42:51 PM

GitHub: 1,207 stars · 146 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 MIATECHPARTNERS/PromptChains, 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 README's opening statement to clarify framework scope

    Why:

    CURRENT
    # ChatGPT Queue Prompts - used for bulk prompting in ChatGPT Queue

ChatGPT Queue Prompts is a collection of prompt chains designed to enhance interactions with large language models (LLMs) like ChatGPT with the use of ChatGPT Queue.
    COPY-PASTE FIX
    # PromptChains: A Declarative Framework for LLM Prompt Workflows

PromptChains provides a powerful, declarative framework for building complex, multi-step prompt workflows for Large Language Models (LLMs). It enables developers to chain prompts, manage context, and define intricate logic to maximize intelligence and results from models like ChatGPT. While designed for broad applicability, PromptChains can be seamlessly integrated with tools like the ChatGPT Queue extension for bulk prompting and job-focused tasks.
  • hightopics#2
    Add relevant topics to the repository

    Why:

    COPY-PASTE FIX
    llm, prompt-engineering, prompt-chaining, ai-framework, workflow-automation, agentic-ai, generative-ai
  • highlicense#3
    Add a LICENSE file to the repository

    Why:

    COPY-PASTE FIX
    Create a `LICENSE` file in the repository root containing the text of a standard open-source license, such as the MIT License.

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 MIATECHPARTNERS/PromptChains
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
LangChain
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. LangChain · recommended 1×
  2. LlamaIndex · recommended 1×
  3. Haystack · recommended 1×
  4. OpenAI API · recommended 1×
  5. PromptFlow · recommended 1×
  • CATEGORY QUERY
    How to chain prompts for large language models to improve context and performance?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. LlamaIndex
    3. Haystack
    4. OpenAI API
    5. PromptFlow
    6. Guardrails AI
    7. DSPy

    AI recommended 7 alternatives but never named MIATECHPARTNERS/PromptChains. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking a tool to automate multi-step prompting workflows for AI assistants efficiently.
    you: not recommended
    AI recommended (in order):
    1. LangChain (langchain-ai/langchain)
    2. LlamaIndex (run-llama/llama_index)
    3. Microsoft Semantic Kernel (microsoft/semantic-kernel)
    4. PromptLayer
    5. Haystack (deepset-ai/haystack)
    6. OpenAI Assistants API

    AI recommended 6 alternatives but never named MIATECHPARTNERS/PromptChains. 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 MIATECHPARTNERS/PromptChains?
    pass
    AI named MIATECHPARTNERS/PromptChains explicitly

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

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

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

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MIATECHPARTNERS/PromptChains — 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