RRepoGEO

REPOGEO REPORT · LITE

ace-agent/ace

Default branch main · commit bcb7cea0 · scanned 6/21/2026, 5:28:46 AM

GitHub: 1,162 stars · 148 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 ace-agent/ace, 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
    Clarify the purpose of ACE's agentic architecture in the README

    Why:

    CURRENT
    ACE (Agentic Context Engineering) is a framework that enables large language models to self-improve by treating contexts as evolving playbooks that accumulate, refine, and organize strategies through a modular process of generation, reflection, and curation.
    COPY-PASTE FIX
    ACE (Agentic Context Engineering) is a framework that enables large language models to self-improve by treating contexts as evolving playbooks that accumulate, refine, and organize strategies through a modular process of generation, reflection, and curation. Unlike fixed-role multi-agent systems, ACE's three-role architecture (Generator, Reflector, Curator) is specifically designed for the iterative evolution and refinement of contexts, not for general task execution by domain-specific agents.
  • hightopics#2
    Add relevant topics to the repository

    Why:

    COPY-PASTE FIX
    llm-agents, agentic-ai, context-engineering, self-improving-llm, language-models, ai-framework, context-management, brevity-bias, context-collapse, llm-ops
  • mediumhomepage#3
    Populate the repository homepage field

    Why:

    COPY-PASTE FIX
    https://deepwiki.com/ace-agent/ace

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 ace-agent/ace
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. OpenAI API · recommended 2×
  4. Haystack · recommended 1×
  5. AutoGPT · recommended 1×
  • CATEGORY QUERY
    How can I build self-improving language agents that manage evolving contexts effectively?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. LlamaIndex
    3. Haystack
    4. AutoGPT
    5. BabyAGI
    6. OpenAI API
    7. Hugging Face Transformers
    8. Hugging Face Datasets
    9. Ray
    10. Ray RLlib
    11. Ray Tune

    AI recommended 11 alternatives but never named ace-agent/ace. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What tools help avoid context collapse and brevity bias in large language model applications?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. LlamaIndex
    3. Pinecone
    4. Weaviate
    5. ChromaDB
    6. OpenAI API
    7. GPT-4
    8. Claude 3 Opus
    9. Vellum
    10. Humanloop
    11. Weights & Biases

    AI recommended 11 alternatives but never named ace-agent/ace. 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 ace-agent/ace?
    pass
    AI did not name ace-agent/ace — 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 ace-agent/ace in production, what risks or prerequisites should they evaluate first?
    pass
    AI named ace-agent/ace 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 ace-agent/ace solve, and who is the primary audience?
    pass
    AI named ace-agent/ace explicitly

    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 ace-agent/ace. 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/ace-agent/ace.svg)](https://repogeo.com/en/r/ace-agent/ace)
HTML
<a href="https://repogeo.com/en/r/ace-agent/ace"><img src="https://repogeo.com/badge/ace-agent/ace.svg" alt="RepoGEO" /></a>
Pro

Subscribe to Pro for deep diagnoses

ace-agent/ace — 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