RRepoGEO

REPOGEO REPORT · LITE

context-labs/HALO

Default branch main · commit 68309f28 · scanned 6/18/2026, 1:17:08 AM

GitHub: 877 stars · 62 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
30 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 0 warn · 1 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 context-labs/HALO, 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
    Reposition README H1 to clarify HALO's purpose and avoid ZKP/Cosmos confusion

    Why:

    CURRENT
    <h1 align="center"> <br> <a href="https://github.com/context-labs/uwu"></a> <br> HALO <br> </h1> <h4 align="center">✨ RLM-based Automatic Agent Optimization Loop ✨</h4>
    COPY-PASTE FIX
    <h1 align="center">HALO: Hierarchical Agent Loop Optimizer for Self-Improving AI Agents</h1> <h4 align="center">✨ RLM-based Automatic Agent Optimization Loop ✨</h4>
  • hightopics#2
    Add specific topics to improve AI categorization and recall

    Why:

    CURRENT
    (none)
    COPY-PASTE FIX
    ai-agents, agent-optimization, reinforcement-learning, machine-learning, rlm, hierarchical-agents, self-improving-agents, agent-framework, python
  • highlicense#3
    Add a LICENSE file to clarify usage terms

    Why:

    CURRENT
    (no LICENSE file detected — the repo has no recognizable license)
    COPY-PASTE FIX
    Add a LICENSE file (e.g., MIT, Apache-2.0, or GPL-3.0) to the repository root, or explicitly state the license(s) in the README if a custom license is intended.

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 context-labs/HALO
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Stable Baselines3
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Stable Baselines3 · recommended 2×
  2. Ray RLlib · recommended 1×
  3. modAL · recommended 1×
  4. scikit-learn · recommended 1×
  5. MLflow · recommended 1×
  • CATEGORY QUERY
    How can I automatically improve the performance of my AI agents over time?
    you: not recommended
    AI recommended (in order):
    1. Ray RLlib
    2. Stable Baselines3
    3. modAL
    4. scikit-learn
    5. MLflow
    6. Kubeflow
    7. Weights & Biases
    8. Optuna
    9. Ray Tune
    10. DVC
    11. Git LFS

    AI recommended 11 alternatives but never named context-labs/HALO. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What tools help build self-optimizing hierarchical agent systems using reinforcement learning?
    you: not recommended
    AI recommended (in order):
    1. Ray RLLib
    2. DeepMind Acme
    3. OpenAI Baselines
    4. Stable Baselines3
    5. TensorFlow Agents (TF-Agents)
    6. PyTorch-Lightning
    7. Gymnasium
    8. PettingZoo
    9. Unity ML-Agents

    AI recommended 9 alternatives but never named context-labs/HALO. This is the gap to close.

    Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

  • Metadata completeness
    fail

    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 context-labs/HALO?
    pass
    AI named context-labs/HALO explicitly

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

  • If a team adopts context-labs/HALO in production, what risks or prerequisites should they evaluate first?
    pass
    AI named context-labs/HALO 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 context-labs/HALO solve, and who is the primary audience?
    pass
    AI named context-labs/HALO explicitly

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

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context-labs/HALO — 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