RRepoGEO

REPOGEO REPORT · LITE

Arthur-Ficial/apfel

Default branch main · commit de10a762 · scanned 6/25/2026, 11:11:14 PM

GitHub: 5,869 stars · 225 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)

3 ready scans. Expand the table below for newest-first rows (10 per page, paginated).

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 Arthur-Ficial/apfel, 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 H1 to specify category and function

    Why:

    CURRENT
    # apfel

### The free AI already on your Mac.
    COPY-PASTE FIX
    # apfel: On-device LLM CLI & OpenAI-compatible Server for Apple Intelligence

### The free AI already on your Mac.
  • mediumreadme#2
    Add a 'What is apfel?' section to the README

    Why:

    COPY-PASTE FIX
    ## What is apfel?

Apfel is a command-line interface (CLI) tool and an OpenAI-compatible local server that leverages the built-in Large Language Model (LLM) capabilities of Apple Intelligence on macOS. It runs 100% on-device, requiring no API keys, cloud services, or additional downloads.
  • mediumreadme#3
    Add a 'Why apfel?' or 'Key Features' section to highlight differentiators

    Why:

    COPY-PASTE FIX
    ## Why apfel?

*   **100% On-Device:** Utilizes Apple Intelligence's built-in LLM, ensuring privacy and no cloud dependency.
*   **Zero Setup:** No downloads, API keys, or complex configurations needed—it's already on your Mac.
*   **OpenAI-Compatible Server:** Seamlessly integrate with existing OpenAI SDKs and tools locally.
*   **UNIX Tool:** Pipe-friendly CLI for scripting and automation.
*   **Tool Calling:** Supports advanced AI capabilities in all contexts.

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 Arthur-Ficial/apfel
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Ollama
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Ollama · recommended 2×
  2. LM Studio · recommended 2×
  3. Jan · recommended 2×
  4. LocalAI · recommended 2×
  5. llama.cpp · recommended 1×
  • CATEGORY QUERY
    How to run a large language model locally on my macOS device without cloud dependency?
    you: not recommended
    AI recommended (in order):
    1. Ollama
    2. LM Studio
    3. Jan
    4. LocalAI
    5. llama.cpp
    6. MLC LLM

    AI recommended 6 alternatives but never named Arthur-Ficial/apfel. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking an OpenAI-compatible local server to develop AI applications on Apple Silicon.
    you: not recommended
    AI recommended (in order):
    1. Ollama
    2. LM Studio
    3. LocalAI
    4. vLLM
    5. Jan

    AI recommended 5 alternatives but never named Arthur-Ficial/apfel. 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 Arthur-Ficial/apfel?
    pass
    AI named Arthur-Ficial/apfel explicitly

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

  • If a team adopts Arthur-Ficial/apfel in production, what risks or prerequisites should they evaluate first?
    pass
    AI named Arthur-Ficial/apfel 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 Arthur-Ficial/apfel solve, and who is the primary audience?
    pass
    AI did not name Arthur-Ficial/apfel — 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?

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Arthur-Ficial/apfel — 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