RRepoGEO

REPOGEO REPORT · LITE

Forward-Future/loopy

Default branch main · commit cc7cb171 · scanned 7/1/2026, 1:33:31 AM

GitHub: 2,210 stars · 195 forks

AI VISIBILITY SCORE
33 /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
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 Forward-Future/loopy, 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 its purpose for AI agents

    Why:

    CURRENT
    # Loop Library

Loop Library has two separate but related parts in this repository:

| Part | What it is | Where it lives |
| | | |
| **Loop Library website** | The public catalog where people and agents can browse published loops, read them, and copy their prompts. No installation is required. | Live website · all website code under [`loop-library/`](loop-library/) (shell in [`loop-library/site/`](loop-library/site/), database and rendering in [`loop-library/worker/`](loop-library/worker/)) |
| **Loopy skill** | An optional installable guide that helps an AI agent discover, find, audit, repair, craft, run, debrief, or prepare loops for publication. It uses the website's live catalog when recommending or publishing loops. | source in [`skills/loopy/`](skills/loopy/) |
    COPY-PASTE FIX
    # Loop Library: A Skill and Catalog for Repeatable AI Agent Workflows

Loopy is a specialized library and installable skill designed to empower AI agents to discover, adapt, and design repeatable workflows, known as "loops," for complex tasks. It provides both a public catalog of published loops and an optional skill that guides agents through finding, auditing, crafting, and running these workflows.

Loop Library has two separate but related parts in this repository:

| Part | What it is | Where it lives |
| | | |
| **Loop Library website** | The public catalog where people and agents can browse published loops, read them, and copy their prompts. No installation is required. | Live website · all website code under [`loop-library/`](loop-library/) (shell in [`loop-library/site/`](loop-library/site/), database and rendering in [`loop-library/worker/`](loop-library/worker/)) |
| **Loopy skill** | An optional installable guide that helps an AI agent discover, find, audit, repair, craft, run, debrief, or prepare loops for publication. It uses the website's live catalog when recommending or publishing loops. | source in [`skills/loopy/`](skills/loopy/) |
  • mediumreadme#2
    Add a 'Comparison' section to the README

    Why:

    COPY-PASTE FIX
    ## Why Loopy? (Compared to X, Y, Z)

[Add a section here explaining how Loopy specifically focuses on repeatable AI agent loops and workflows, differentiating it from general LLM frameworks like LangChain or broader workflow orchestration tools like Apache Airflow. Emphasize its unique value proposition for agent-centric task design and adaptation.]
  • lowtopics#3
    Expand repository topics with more specific AI agent workflow terms

    Why:

    CURRENT
    agent-skills, agentic-workflows, ai-agents, automation, codex, prompt-engineering
    COPY-PASTE FIX
    agent-skills, agentic-workflows, ai-agents, automation, codex, prompt-engineering, agent-orchestration, llm-agent-design, prompt-chaining, agent-feedback-loops

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 Forward-Future/loopy
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. Apache Airflow · recommended 1×
  3. Prefect · recommended 1×
  4. Metaflow · recommended 1×
  5. Kubeflow Pipelines · recommended 1×
  • CATEGORY QUERY
    How to design and manage repeatable workflows for AI agents effectively?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. Apache Airflow
    3. Prefect
    4. Metaflow
    5. Kubeflow Pipelines
    6. Temporal

    AI recommended 6 alternatives but never named Forward-Future/loopy. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Tool to help AI agents discover and adapt existing prompt engineering patterns?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. LlamaIndex
    3. PromptPerfect
    4. OpenAI API
    5. Haystack
    6. Weights & Biases

    AI recommended 6 alternatives but never named Forward-Future/loopy. 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 Forward-Future/loopy?
    pass
    AI did not name Forward-Future/loopy — 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 Forward-Future/loopy in production, what risks or prerequisites should they evaluate first?
    pass
    AI named Forward-Future/loopy 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 Forward-Future/loopy solve, and who is the primary audience?
    pass
    AI named Forward-Future/loopy explicitly

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

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Forward-Future/loopy — 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