RRepoGEO

REPOGEO REPORT · LITE

daveshap/ACE_Framework

Default branch main · commit c6693ee2 · scanned 6/29/2026, 9:38:14 PM

GitHub: 1,501 stars · 216 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 daveshap/ACE_Framework, 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 H1 and add an introductory paragraph

    Why:

    CURRENT
    # Project Principles
    COPY-PASTE FIX
    # ACE Framework: 100% Local and Open Source Autonomous Cognitive Entities

ACE (Autonomous Cognitive Entities) is a framework for building advanced AI agents that operate entirely on local hardware, without reliance on cloud providers or proprietary services. It emphasizes a comprehensive cognitive architecture to enable complex, multi-step reasoning and task execution within a fully open-source ecosystem.

## Project Principles
  • mediumhomepage#2
    Add a homepage URL to the repository metadata

    Why:

    COPY-PASTE FIX
    https://github.com/daveshap/ACE_Framework

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 daveshap/ACE_Framework
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. LangChain · recommended 2×
  3. Open Assistant · recommended 1×
  4. Llama.cpp · recommended 1×
  5. Haystack · recommended 1×
  • CATEGORY QUERY
    Framework for building autonomous AI agents that run entirely on local, open source hardware?
    you: not recommended
    AI recommended (in order):
    1. Open Assistant
    2. Llama.cpp
    3. Ollama
    4. LangChain
    5. Haystack
    6. AutoGPT
    7. MicroPython
    8. CircuitPython
    9. TensorFlow Lite Micro
    10. Edge Impulse
    11. ROS (Robot Operating System)
    12. OpenCV
    13. YOLOv8

    AI recommended 13 alternatives but never named daveshap/ACE_Framework. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    How to develop self-hosted AI assistants without relying on specific cloud providers or vendors?
    you: not recommended
    AI recommended (in order):
    1. LocalAI
    2. Ollama
    3. LM Studio
    4. PrivateGPT
    5. LangChain
    6. LlamaIndex
    7. Hugging Face `transformers` library
    8. TensorFlow
    9. PyTorch

    AI recommended 9 alternatives but never named daveshap/ACE_Framework. 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 daveshap/ACE_Framework?
    pass
    AI named daveshap/ACE_Framework explicitly

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

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

Embed your GEO score

Drop this badge into the README of daveshap/ACE_Framework. 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)
[![RepoGEO](https://repogeo.com/badge/daveshap/ACE_Framework.svg)](https://repogeo.com/en/r/daveshap/ACE_Framework)
HTML
<a href="https://repogeo.com/en/r/daveshap/ACE_Framework"><img src="https://repogeo.com/badge/daveshap/ACE_Framework.svg" alt="RepoGEO" /></a>
Pro

Subscribe to Pro for deep diagnoses

daveshap/ACE_Framework — 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