RRepoGEO

REPOGEO REPORT · LITE

hexo-ai/sia

Default branch main · commit 01939270 · scanned 6/15/2026, 5:12:08 PM

GitHub: 1,719 stars · 199 forks

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 hexo-ai/sia, 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
    Add a disclaimer to the README about Hexo blog platform

    Why:

    CURRENT
    # SIA (Self-Improving AI)
    COPY-PASTE FIX
    # SIA (Self-Improving AI)

**Note:** This project is a Self-Improving AI framework and is not related to the Hexo blogging platform.
  • hightopics#2
    Add descriptive topics to the repository

    Why:

    CURRENT
    (none)
    COPY-PASTE FIX
    self-improving-ai, ai-framework, machine-learning, agent-based-ai, llm, model-optimization, benchmark-tasks, autonomous-ai
  • mediumreadme#3
    Highlight SIA's core differentiator in the README introduction

    Why:

    CURRENT
    Official implementation of **SIA: Self Improving AI with Harness & Weight Updates** (Hebbar et al., 2026) — a self-improving loop where a language-model agent updates both the harness and the weights of a task-specific agent.
    COPY-PASTE FIX
    Official implementation of **SIA: Self Improving AI with Harness & Weight Updates** (Hebbar et al., 2026) — a novel self-improving loop where a language-model agent uniquely updates *both* the harness and the weights of a task-specific agent, a key differentiator for achieving significant performance gains.

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 hexo-ai/sia
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Ludwig
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Ludwig · recommended 1×
  2. AutoKeras · recommended 1×
  3. FLAML · recommended 1×
  4. Google Cloud AutoML · recommended 1×
  5. H2O.ai · recommended 1×
  • CATEGORY QUERY
    Seeking a framework to autonomously improve AI model performance on benchmark tasks.
    you: not recommended
    AI recommended (in order):
    1. Ludwig
    2. AutoKeras
    3. FLAML
    4. Google Cloud AutoML
    5. H2O.ai
    6. TPOT
    7. Optuna

    AI recommended 7 alternatives but never named hexo-ai/sia. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are the best tools for implementing self-improving loops for AI agents?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. LlamaIndex
    3. Ray
    4. OpenAI Gym
    5. PyTorch
    6. TensorFlow
    7. MLflow
    8. Weights & Biases

    AI recommended 8 alternatives but never named hexo-ai/sia. 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 hexo-ai/sia?
    pass
    AI did not name hexo-ai/sia — 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 hexo-ai/sia in production, what risks or prerequisites should they evaluate first?
    pass
    AI named hexo-ai/sia 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 hexo-ai/sia solve, and who is the primary audience?
    pass
    AI named hexo-ai/sia explicitly

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

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hexo-ai/sia — 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