RRepoGEO

REPOGEO REPORT · LITE

daveshap/ACE_Framework

Default branch main · commit c6693ee2 · scanned 5/18/2026, 2:52:57 PM

GitHub: 1,504 stars · 219 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 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

3 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION
  • hightopics#1
    Add relevant topics to the repository

    Why:

    COPY-PASTE FIX
    autonomous-agents, local-ai, open-source, ai-framework, cognitive-architecture, llm-agents, no-cloud, self-improving-agents
  • highreadme#2
    Add a concise 'what it is' statement at the top of the README

    Why:

    CURRENT
    The README currently starts with '# Project Principles'.
    COPY-PASTE FIX
    Add the following as the very first lines of the README, before '# Project Principles':

# ACE Framework: 100% Local & Open Source Autonomous Cognitive Entities

ACE (Autonomous Cognitive Entities) is a framework for building intelligent agents that can reason, plan, and self-improve, designed to run entirely on local hardware without reliance on cloud services or specific vendor APIs. It emphasizes a modular cognitive architecture for persistent, autonomous operation.
  • mediumhomepage#3
    Add a homepage URL to the repository metadata

    Why:

    COPY-PASTE FIX
    Add the official project website or documentation URL (e.g., `https://aceframework.org` or `https://github.com/daveshap/ACE_Framework/wiki`) to the repository's 'About' section.

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
LangChain
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. LangChain · recommended 2×
  2. LlamaIndex · recommended 2×
  3. AutoGPT · recommended 1×
  4. CrewAI · recommended 1×
  5. deepset/Haystack · recommended 1×
  • CATEGORY QUERY
    Looking for an open source framework to build autonomous agents that run entirely on local hardware.
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. LlamaIndex
    3. AutoGPT
    4. CrewAI
    5. Haystack (deepset/Haystack)
    6. AgentGPT

    AI recommended 6 alternatives but never named daveshap/ACE_Framework. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    How to develop AI agents without relying on cloud services or specific vendor APIs?
    you: not recommended
    AI recommended (in order):
    1. LlamaIndex
    2. LangChain
    3. Ollama
    4. Hugging Face Transformers
    5. Faiss
    6. NLTK
    7. spaCy

    AI recommended 7 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 named daveshap/ACE_Framework explicitly

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

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MARKDOWN (README)
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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