RRepoGEO

REPOGEO REPORT · LITE

Xiangyue-Zhang/auto-deep-researcher-24x7

Default branch main · commit dbf3df81 · scanned 7/1/2026, 3:53:10 PM

GitHub: 1,229 stars · 100 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 Xiangyue-Zhang/auto-deep-researcher-24x7, 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
    Strengthen README's opening to emphasize autonomous AI agent for research

    Why:

    CURRENT
    An AI agent that autonomously runs your deep learning experiments 24/7 while you sleep.
    COPY-PASTE FIX
    Deep Researcher Agent is an **autonomous AI agent** specifically designed to conduct **deep learning research** 24/7. Unlike traditional MLOps tools or experiment trackers, it proactively designs, executes, and analyzes experiments, acting as your intelligent research partner.
  • mediumtopics#2
    Add more specific "agent" and "research" topics

    Why:

    CURRENT
    ai-agent, autonomous-agent, claude-code, deep-learning, experiment-automation, gpu, hyperparameter-tuning, llm-agent, machine-learning, mlops, pytorch, research-automation
    COPY-PASTE FIX
    ai-agent, autonomous-agent, agentic-ai, claude-code, deep-learning, deep-learning-research, experiment-automation, experiment-design, gpu, hyperparameter-tuning, llm-agent, machine-learning, mlops, ml-research-agent, pytorch, research-automation
  • mediumreadme#3
    Add a "Comparison" section to differentiate from MLOps tools

    Why:

    COPY-PASTE FIX
    ## Why Deep Researcher Agent? (vs. MLflow, Weights & Biases, Ray Tune)
Deep Researcher Agent is an **autonomous AI agent** that *conducts* deep learning research, rather than just *tracking* or *orchestrating* experiments. While tools like MLflow and Weights & Biases excel at logging, visualizing, and managing experiment metadata, and Ray Tune focuses on hyperparameter optimization, Deep Researcher Agent goes further by autonomously *designing* experiments, *interpreting* results, and *iterating* on research hypotheses 24/7. It can integrate with these tools for enhanced tracking, but its core function is agentic research automation.

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 Xiangyue-Zhang/auto-deep-researcher-24x7
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
MLflow
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. MLflow · recommended 2×
  2. Ray Tune · recommended 2×
  3. Weights & Biases · recommended 1×
  4. Hyperopt · recommended 1×
  5. Optuna · recommended 1×
  • CATEGORY QUERY
    How can I automate deep learning experiment execution and hyperparameter tuning continuously?
    you: not recommended
    AI recommended (in order):
    1. Weights & Biases
    2. MLflow
    3. Hyperopt
    4. Optuna
    5. Ray Tune
    6. Comet ML
    7. Katib
    8. SigOpt

    AI recommended 8 alternatives but never named Xiangyue-Zhang/auto-deep-researcher-24x7. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What autonomous AI agents exist for running machine learning research experiments 24/7?
    you: not recommended
    AI recommended (in order):
    1. Kubeflow Pipelines
    2. MLflow
    3. Ray Tune
    4. Google Cloud AutoML
    5. H2O.ai AutoML
    6. AutoKeras
    7. AutoGluon
    8. NNI - Neural Network Intelligence
    9. OpenAI Gym
    10. Stable Baselines3
    11. AutoGPT
    12. BabyAGI

    AI recommended 12 alternatives but never named Xiangyue-Zhang/auto-deep-researcher-24x7. 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 Xiangyue-Zhang/auto-deep-researcher-24x7?
    pass
    AI named Xiangyue-Zhang/auto-deep-researcher-24x7 explicitly

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

  • If a team adopts Xiangyue-Zhang/auto-deep-researcher-24x7 in production, what risks or prerequisites should they evaluate first?
    pass
    AI named Xiangyue-Zhang/auto-deep-researcher-24x7 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 Xiangyue-Zhang/auto-deep-researcher-24x7 solve, and who is the primary audience?
    pass
    AI did not name Xiangyue-Zhang/auto-deep-researcher-24x7 — 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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Xiangyue-Zhang/auto-deep-researcher-24x7 — 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